Journal of Computational Methods in Sciences and Engineering - Volume 23, issue 3

Authors: Zang, Xiaokui | Cao, Zhiqiang | Xiao, Mengshi | Yang, Xiaoou

Article Type: Research Article

Abstract: Transformers play a crucial role in ensuring the safety of power grids. It is of great value to diagnose faults using the large amount of power data generated by the grid. It is possible to detect internal latent faults in transformers in advance of their occurrence if the normal operating condition of the transformer is detected in a timely manner. To perform online fault diagnosis of grid current transformers, we combine the Transformer and BiGRU methods. There is a temporal component to the fault input sample sequences. By using Transformer’s multi-headed attention mechanism to extract deep features from fault input …sample sequences, the temporal association between latent variables can be fully exploited. As a result of the extraction of features, BiGRU is used to generate fault category coding as an output. The experimental results indicate that using the proposed algorithm achieves better results than using a single model, which is useful for the study and application of fault diagnosis in power grids for current transformers. Show more

Keywords: Current transformer, transformer, BiGRU, latent variable, fault sample sequence, fault category coding

DOI: 10.3233/JCM-226763

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1137-1149, 2023

Authors: Yu, Jun | Chen, Zongren | Jiang, Xiaobo | Wang, Bo

Article Type: Research Article

Abstract: Aiming at the problems of high feature mismatch rate and low matching efficiency in the current virtual image multi feature matching algorithm, a virtual image multi feature matching algorithm based on 3D scene reconstruction is proposed. Firstly, in the 3D scene reconstruction, the virtual image is preprocessed to eliminate the noise in the virtual image, avoid the noise interference in the compression process, and improve the signal-to-noise ratio of the image; Secondly, the de-noising virtual image is enhanced to enhance the details of the image; Finally, the corresponding information feature vector is constructed from the information features extracted from the …virtual image, and the virtual image multi feature matching algorithm is completed. Experiments show that the multi feature matching rate of the designed algorithm is high, the error matching rate is low, the maximum spatial distortion rate is only 0.6%, and the compressed image quality and matching performance are good. Show more

Keywords: 3D scene reconstruction, virtual image, multi feature matching algorithm, signal to noise ratio, spatial distortion rate

DOI: 10.3233/JCM-226757

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1151-1163, 2023

Authors: Zhou, Ying | Liu, Yongfu | Li, Qiang | Fan, Wenyan | Pan, Xiaoli | Yu, Wangxin

Article Type: Research Article

Abstract: Microwave vacuum drying of pineapple slices was carried out to investigate the microwave power degree on the drying kinetics and heat mass transfer characteristics. Numerical simulation and bench test were used to study the variation characteristic of microwave volumetric heating and temperature and moisture during the drying process, and the best drying model was selected. The result shows that the drying process of the pineapple slices belonged to the falling rate period without constant drying stage; Among 6 common thin layer drying kinetic models, the mean values of R 2 were maximum, χ 2 …and RMSE for the Two-term exponential model were minimum, which were 0.9993, 0.000107 and 0.00839, respectively. As the temperature rose to 40∼ 45 ∘ C at the late stage of drying, the thermal runaway phenomenon appeared, and the internal temperature of pineapple slices rose sharply. Hot spots appeared at the center and edge of pineapple at the late stage of drying, and it generated by microwave volumetric heating focusing. The predicted values of moisture ratio (MR) obtained from COMSOL simulation showed good consistency with the Two-term exponential model and the experimental. In order to improve the drying quality of the pineapple, the microwave power should be varied and reasonable interval to make the drying temperature lower than the thermal runaway temperature range. Show more

Keywords: Pineapple, microwave vacuum drying, numerical simulation, heat and mass transfer

DOI: 10.3233/JCM-226758

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1165-1178, 2023

Authors: Liu, Xiaomei | Yue, Jianlong

Article Type: Research Article

Abstract: This paper uses a real-time anomaly attack detection based on improved variable length sequences and data mining. The method is mainly used for host-based intrusion detection systems on Linux or Unix platforms which use shell commands. The algorithm first generates a stream of command sequences with different lengths and subsumes them into a generic sequence library, de-duplicats and sortes shell command sequences. The shell command sequences are then stratified according to their weighted frequency of occurrence to define the state. Next, the behavioural patterns of normal users are mined to output the state stream and a Markov chain is constructed. …Then, the state sequences are calculated based on a primary probability distribution and a transfer probability matrix. The System will check decision values of the short sequence stream. Finally, the decision values of the behavioural sequences are analysed to determine whether the current session user is behaving abnormally. The improved algorithm introduces the concept of multi-order frequencies and proposes a new separation mechanism. The extension module is integrated into the variable length model. By comparing the performance of the old and new separation mechanisms on the SEA dataset and the self-made dataset (SD), it is found that the improved model greatly improves the performance of the model and shortens the running time. Show more

Keywords: Variable length model, Markov, new separation mechanism, weighted frequency

DOI: 10.3233/JCM-226663

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1179-1195, 2023

Authors: Hong, Liang | Wu, Kaibin | Yue, Mengmeng

Article Type: Research Article

Abstract: For the power transmission tower shared equipment, there are strong current wireless interference and complex grounding environment, which leads to problems such as unstable operation of the shared equipment. Based on the multi-grade surge protector and new grounding technology, through the impulse experiments, we apply simulated lightning current generated from combined wave generator (1.2/50 μ s, 8/20 μ s) on the modle, and an oscilloscope is used to collect residual voltage and current data to calculate the absorbed energy of the grounding unit. It is concluded that when the impulse voltage is between 300 V and 3500 …V, as the impulse voltage increases, after passing through the multi-grade surge protector and grounding unit, the residual voltage and current value continue to increase, and the residual voltage value is 23.4 V–29.6 V increases linearly, and the increase is small; the internal resistance of the grounding unit decreases with the increase of the impulse voltage. The energy absorbed by the grounding unit is positively correlated with the impulse voltage and negatively correlated with the internal resistance, and its energy absorption percentage decays linearly. The multi-grade surge protector can effectively clamp the residual voltage value within a safe value, and its discharge effect is better than that of the traditional protection mode. It provides a theoretical basis and data reference for the lightning protection and anti-interference projects of the actual transmission tower sharing equipment, and has certain practical value. Show more

Keywords: The power transmission tower shared equipment, the multi-grade surge protector, new grounding technology, lightning current, energy absorbed

DOI: 10.3233/JCM-226682

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1197-1207, 2023

Authors: Zhan, Keqiang

Article Type: Research Article

Abstract: Image fusion can extract the useful information of each channel about the same target to the maximum extent, and get high quality image. However, in this process, the image quality may be affected by noise and reduced. To reduce the image noise’s influence on the image fusion effect as well as improve the image fusion quality, a multi sensor moving image fusion analysis algorithm on the basis of neural network technology is proposed. This study designed a window adaptive strategy, use the probability density function, and built an impulse noise model, and use this model to divide each pixel in …the image into noise points or signal points to obtain image impulse noise detection results, and use bilateral filtering algorithm to achieve image denoising processing; The fruit fly optimization algorithm is adopted to detect the edge of the multi sensor moving image, extract the image’s main edge points, and remove the detail edge points and noise points; nonlinear convolutional layer is used to replace most fusion layers to improve the dense network model, and the cross-entropy loss is used as the loss function in training the network, then use guided filters to generate guide maps, and generate final fusion images. According to experimental results, the noise detection method in this paper can also maintain 79.21% non-noise extraction rate under the noise density of 0.7. The highest correlation coefficient between the proposed algorithm and the standard image is 37.41. Its peak signal-to-noise ratio is as low as 0.09 and as high as 0.52. It has a minimum root mean square error of 8.52. The above values are better than other measured methods, and its edge miss rate can be as low as 1%, the image resolution is higher. It can be seen that its image denoising effect is better. Image denoising effect, and low edge missed detection rate, which effectively improves the effect of image fusion. Show more

Keywords: Neural network technology, multi sensor, image fusion, impulse noise model, fruit fly optimization algorithm, improved dense network

DOI: 10.3233/JCM-226704

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1209-1224, 2023

Authors: Dong, Yongjian | Ye, Qinrong

Article Type: Research Article

Abstract: With the rapid development of artificial intelligence and the continuous improvement of machine learning technology, speech recognition technology is also developing rapidly and the recognition accuracy is improving to meet the higher requirements of people for smart home devices, and combining smart home with voice recognition technology is an inevitable trend for future development. This study aims to propose a speech fuzzy enhancement algorithm based on neural network for smart home interactive speech recognition technology, so the study proposes a combination of fuzzy neural network algorithm (FNN) and stacked self-encoder (SAE) to form SAE-FNN algorithm, which has better non-linear characteristics …and can better achieve feature learning, thus improving the performance of the whole system. The results show that with the SAE-FNN algorithm, the maximum relative error absolute value, average relative error and root mean square error are 0.355, 0.063 and 0.978, which are significantly higher than the other two individual algorithms, and the noise of the sound signal has little effect on the SAE-FNN algorithm. Therefore, it can be seen that the proposed SAE-FNN algorithm has excellent noise immunity performance. In summary, it can be seen that this neural network-based speech fuzzy enhancement algorithm for smart home interaction is extremely feasible. Show more

Keywords: Smart home, fuzzy neural network algorithm, stacked self encoder, speech emotion recognition, speech recognition, feature extraction

DOI: 10.3233/JCM-226702

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1225-1236, 2023

Authors: Chai, Xiaojie | Wang, Rongshen | Wang, Junming | Zhang, Riqiang

Article Type: Research Article

Abstract: In order to improve the image quality, reduce the image noise and improve the image definition, the image depth fusion processing is realized by using the sp CNN network (Super pixel level convolution neural network, sp CNN). The improved non-local mean method is used to de-noise the image to highlight the role of the center pixel of the image block; the de-noised image is segmented by the improved CV model (Chan-Vese, CV), and the globally optimal multi-scale image segmentation result is obtained after optimization; From the perspective of regional features, the similarity measurement of image regions is carried out to …realize image preprocessing. The sp-CNN network is constructed, and with the help of the idea of pyramid pooling, the average pooling is used to extract the features of each layer from the global and local levels of the convolutional features, and the training data set is generated for training, thereby realizing multi-scale image fusion. The experimental results show that the optimal value of the root mean square error index of the proposed method is 0.58. The optimal value of structural similarity index is 41.22. On the average slope index, the optimal value is 21.39. The optimal value of cross entropy index is 2.21. This shows that the proposed method has high image definition and good visual effect, which verifies the effectiveness of the method. Show more

Keywords: Superpixel-level convolutional neural network, image fusion, improved CV model, improved non-local mean, pyramid pooling

DOI: 10.3233/JCM-226706

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1237-1250, 2023

Authors: Shen, Yang

Article Type: Research Article

Abstract: Mechanical fault detection has an important influence on production schedule and efficiency. With the development of intelligent technology, more and more intelligent detection technologies are applied to mechanical fault detection. In order to detect mechanical faults more efficiently and accurately, this experiment proposes a production knowledge base model based on genetic algorithm (GA algorithm). The model uses the unique biological genetics principle of genetic algorithm to evolve the interested population, and can conduct spatial search to find the global optimal solution. By comparing the performance of GA algorithm model with other similar detection models, it is found that the model …proposed in the experiment has obvious advantages in mechanical fault detection performance. The experimental results show that the maximum accuracy of the GA algorithm is 0.935, 0.074 higher than the support vector machine (SVM) model, 0.118 higher than the linear discriminant analysis (LDA) model, 0.032 higher than the random forest (RF) model, and 0.166 higher than the K nearest neighbor (KNN) model. In addition, the error value of GA algorithm is the lowest among these models, which is 0.028. This proves that the genetic algorithm model has higher diagnostic accuracy and can play an important role in mechanical fault detection. Show more

Keywords: Detection model, genetic algorithm, mechanical fault, production knowledge base

DOI: 10.3233/JCM-226719

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1251-1263, 2023

Authors: Wang, Hui

Article Type: Research Article

Abstract: Purpose: To solve the problems of low integration accuracy and long integration time of traditional prefabricated construction information integration methods. Method: A method of assembling building information integration based on BIM and RFID technology was proposed. By analyzing the information integration principle of BIM RFID (Building Information Modeling Radio Frequency Identification) technology, starting with rfid technology, we use rfid technology to collect the information of prefabricated building components and obtain the coding information of component data. Experiment: Combining Markov model and fuzzy algorithm, the obtained coding information is preprocessed. According to the processing results, statistical feature clustering algorithm is introduced …to integrate the construction information of prefabricated buildings. Result: The precision polyline of the prefabricated building construction information integration method based on BIM and RFID technology showed a steady increase, and it was close to 100% in the later stage. At the same time, the time consumed by this method was within 0.41 s, with high accuracy, high efficiency and high practicability. Show more

Keywords: BIM technology, RFID technology, prefabricated building construction, information integration

DOI: 10.3233/JCM-226720

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1265-1278, 2023

Authors: Chen, Yang | Xie, Yihuai

Article Type: Research Article

Abstract: In order to improve the effect of landscape design, based on the traditional multi-dimensional nonlinear landscape design and RBF neural network, this paper proposes and designs a multi-dimensional nonlinear landscape design method based on neural network. Firstly, the camera parameters are set, the landscape images are collected by UAV, and the collected landscape images are segmented. Landscape image features are extracted according to different classification criteria, and the feature information is used as training samples to train the neural network. Finally, the landscape design parameters are fitted and the results of the landscape design model are output. The experimental results …show that the proposed method has better classification accuracy than the other two traditional landscape image classification algorithms. In different experiments, the landscape image classification accuracy of this method is kept above 85%, while the other two methods are lower. In addition, the regression analysis value and test value of this method also perform well. Finally, given a noisy image, it is found that the text method can effectively remove the noise in the landscape design image, making the image present a clearer landscape layout. Show more

Keywords: Neural network, multi dimension, nonlinearity, landscape design

DOI: 10.3233/JCM-226724

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1279-1293, 2023

Authors: Wang, Fang

Article Type: Research Article

Abstract: The adaptive backstepping control method of permanent magnet motor has the problems of complicated coordinate transformation process and high position tracking error. Based on this, an adaptive backstepping control method of permanent magnet synchronous motor based on RBF is proposed. According to the principle of electrical machinery, the electromagnetic wave and magnetic field data are obtained, and the mathematical model of permanent magnet synchronous motor is constructed. Under the condition of keeping the resultant magnetomotive force after coordinate transformation unchanged, the structure of motor torque neural network is established by RBF method, and the coordinate transformation process is optimized. Through …the compensation control strategy, the adaptive backstepping control mode is designed to realize the adaptive backstepping control of permanent magnet synchronous motor. The simulation results show that the position tracking error of the proposed method is 4.549 mm when the running time is 7 s and 43.699 mm when the running time is 14 s, which proves that the adaptive backstepping control effect of the proposed method is better. Show more

Keywords: RBF, permanent magnet synchronous motor, adaptive, backward control method, CNC machine tools, electromagnetic wave

DOI: 10.3233/JCM-226728

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1295-1305, 2023

Authors: Fan, Xianzheng | Jiao, Xiongfeng | Shuai, Mingming | Qin, Yi | Chen, Jun

Article Type: Research Article

Abstract: Railway transportation is the main means of transportation for people and the main way of logistics transportation, playing an important role in daily life. Therefore, the safety inspection of railway track has been widely valued. The abnormal intelligent detection of rail fasteners is the key content of rail safety detection. The traditional rail fastener detection method is based on machine learning for image recognition, such as SVM, to detect abnormal rail fasteners. But the traditional method has two defects. The first point is that the detection time is long, and the second point is that the detection accuracy is low. …To solve this problem, a rail fastener anomaly detection model based on SVM optimized by IFOA algorithm is proposed. Firstly, the image of rail fastener is collected and filtered; Then, edge detection and image segmentation are performed to obtain the image of the target area; Finally, the HOG feature and LBP feature of the image are extracted, and the improved IFOA-SVM is used to recognize and classify the features, so as to achieve intelligent rail fastener anomaly detection. The experimental results show that when the IACO-SVM model is iterated to 254 times, the fitness value tends to be stable, which is 0.24. The detection accuracy of the model reaches 99.82%, which is higher than the traditional models, and can meet the work requirements of rail fastener anomaly detection. The rail fastener anomaly detection model based on SVM can improve the efficiency of rail fastener anomaly detection, and has a positive effect on the normal operation of railway transportation. However, the number of experimental samples used in the study is limited, which may lead to some errors in the experimental results. Therefore, it is necessary to increase the number of samples in subsequent studies. Show more

Keywords: SVM, rail fasteners, image recognition, HOG, LBP feature

DOI: 10.3233/JCM-226723

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1307-1319, 2023

Authors: Cao, Yimin

Article Type: Research Article

Abstract: As China’s tourism industry is on the right track, the country has gradually paid more attention to the ecological protection of tourism areas. Under the concept of sustainable development, the research on environmental adaptability of tourist attractions has become a hotspot. This study took Huanglongxi Ancient Town in Shuangliu District, Chengdu City, Sichuan Province as the research object, and determined seven ecological protection spaces of Huanglongxi Ancient Town by MSPA method, and then used the landscape connectivity method to identify the priority of ecological sources. The high green space and water are the “source”, and finally the path network is …constructed using space syntax, and the relationship between the flow of people and the path resistance disturbance is calculated. After analysis, it is concluded that Huanglongxi Ancient Town has 2 green spaces with higher priority and 1 water area with higher priority. The route layout can meet the current annual reception volume and will not cause obvious congestion during the daily peak. Huanglongxi Ancient Town has 6 enterprises above designated size and 20,000 square kilometers of arable land. The average dLLC of the green space in Huanglongxi Ancient Town is 19.10, the average dPC is 20.92, the maximum time resistance is 0.951 + 1.703*10 - 7 *V 151.3 , and the maximum time resistance disturbance is 0.999. Huanglongxi Ancient Town can pass between paths 7–8. Add new paths to improve the path situation. Show more

Keywords: MSPA, landscape connectivity, ecological source area, space syntax, path network, environmental adaptability

DOI: 10.3233/JCM-226707

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1321-1333, 2023

Authors: Wang, Hui

Article Type: Research Article

Abstract: With the increasingly rich recreational activities of college students, diversified learning needs and complex physical education resources bring challenges to college physical education. In order to optimize the teaching effect of calisthenics in colleges and universities, this paper proposes a matching method of posture features based on dynamic time warping. Firstly, the dynamic time warping algorithm is introduced, and then the matching model of posture features of calisthenics is constructed on this basis. Finally, the application effect of the model is tested and analyzed. The results show that the model can capture the video frame accurately, and its matching accuracy …reaches 94.8%, which greatly improves the accuracy of aerobics action recognition. Good posture matching effect is conducive to teachers to obtain a clear learning situation of students, and provide a reference for adjusting the teaching progress and teaching methods of calisthenics. Under the teaching mode of this model, the average professional score of the students in calisthenics reaches 85 points, which is 25 points higher than that under the convolutional neural network model. It also proves the validity and feasibility of this method in the course of calisthenics in colleges and universities, which is beneficial to enhance the physical quality of college students and enrich the content of calisthenics teaching. Show more

Keywords: Posture feature, dynamic time regulation, aerobics, intelligent sports, colleges and universities

DOI: 10.3233/JCM-226709

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1335-1347, 2023

Authors: Lv, Dihua

Article Type: Research Article

Abstract: With the development and maturity of virtual reality (VR for short) and artificial intelligence technology, panoramic VR roaming is applied to more and more industries. In the construction engineering industry, due to the complex structure of some key building nodes, the application of panoramic VR roaming technology modeling will play a role in significantly reducing the workload and understanding difficulty of design, construction and management personnel. Therefore, this study improves the parallax map generation method of the belief propagation (BP) algorithm in the panoramic VR roaming to use the form of limit matching and optimizes the energy function and matching …primitives in it, so as to propose a spatial model construction method of the panoramic VR roaming based on the improved BP algorithm. The experimental results show that the panoramic VR roaming space model construction method proposed in this study can significantly improve the quality of spatial modeling of building node images, and the normalized values of structural similarity of VR roaming space models designed based on Improved belief propagation (IBP), GC, BP, and DP algorithms are 3.32, 3.23, 2.96, and 2.84, respectively, when the number of iterations is obtained 200 times, is also the highest among the compared methods, for example, when the number of samples is 400, the calculation time of IBP scheme is 14.73 ± 0.85 min, and the highest time of other three schemes is 6.86 ± 0.67 min. Therefore, this virtual space modeling method is designed to be more suitable for application scenarios that require lower computational timeliness. Show more

Keywords: VR, building nodes, BP algorithm, attention mechanism

DOI: 10.3233/JCM-226695

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1349-1361, 2023

Authors: Huang, Ying | Dong, Gang | Liu, Zhangyin | Zhu, Jiong | Peng, Weidong

Article Type: Research Article

Abstract: With the rapid development of 5G sensors, the development of low cost, low power consumption, and miniaturization is also constantly progressing, and 5G sensor networks have achieved great development. Node positioning technology is an important support for 5G sensors, so it has been a hot research direction in recent years. This article has carried on the basic discussion to the speech broadcasting technology, and introduced the speech broadcasting coding in many aspects, including the development history, the current situation and the compression coding algorithm. This article has launched a basic analysis and discussion on the voice broadcast algorithm, such as …its basic principles and classification. In order to minimize the property losses and casualties caused by urban fires and improve the efficiency and success rate of urban fire emergency systems, it is necessary to be able to query fire information in a timely and effective manner and formulate emergency protection. As we all know, China’s current economic development is in a period of steady improvement, and the process of urbanization is gradually accelerating, especially the number of high-rise and super high-rise buildings has increased significantly. Therefore, once a city fire occurs, it will not only cause huge losses of property, but also may cause a large number of casualties. Although the current fire protection system in Chinese cities is relatively complete, there are still some problems that have not been resolved in actual work, such as insufficient technical equipment and insufficient response speed in some areas due to economic constraints. Therefore, it is very necessary to establish an efficient urban fire emergency information system, not only to be able to query fire information in a timely and effective manner, but also to be able to formulate emergency support plans for specific actual situations. Show more

Keywords: 5G sensor, voice broadcast, urban fire, emergency system

DOI: 10.3233/JCM-226691

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1363-1380, 2023

Authors: Li, Zhen

Article Type: Research Article

Abstract: With the rapid development of network technology and information technology, the amount of information contained in images has increased significantly. How to effectively extract text information from complex images has become the focus of current research in this field. Firstly, the Canny algorithm in the edge detection algorithm is improved and applied to the edge detection of complex images. Then the K-means algorithm is optimized to achieve better clustering effect of pixels. Finally, the text information in the image is extracted from the two. The results show that under the influence of salt and pepper noise from 0% to 90%, …the quality factor obtained by the improved Canny algorithm is at least 0.4, and the detection accuracy is higher; The minimum peak signal-to-noise ratio of the algorithm is 38, and the maximum mean square error is 30, which are both better than the LOG algorithm and the traditional Canny algorithm, and have better noise reduction effect and image fidelity. It is used together in the extraction process of image text information, and the text recognition accuracy rate of the combined algorithm reaches a maximum of 93%, and is stable at more than 90%, indicating that this method has a high text recognition accuracy rate and provides text extraction for complex images. A reference path is available. Show more

Keywords: Edge detection, canny algorithm, text extraction, K-means algorithm

DOI: 10.3233/JCM-226722

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1381-1393, 2023

Authors: Xu, Jing

Article Type: Research Article

Abstract: To solve the problem that the presence of foreign matters in cosmetics will affect the safety and health of consumers and is not conducive to the development of the cosmetics industry, an intelligent identification system for foreign matters in cosmetics is established using the improved BP algorithm. Scan cosmetic samples to identify foreign matters and extract foreign matter features, so as to achieve non-destructive detection of foreign matters in cosmetics. Comparing the traditional BP algorithm, Faster R-CNN algorithm and the improved BP algorithm, the results show that the convergence time of the improved BP algorithm is 60 s and 30 …s earlier than that of the traditional BP algorithm and Faster R-CNN algorithm respectively; Whether there is noise or not, the recognition rate of the improved BP algorithm is always higher than that of the traditional BP algorithm and Faster R-CNN algorithm. The accuracy rate of the improved BP algorithm is between 0.88 and 0.96, the accuracy rate of the traditional BP algorithm is between 0.57 and 0.75, and the accuracy rate of the Faster R-CNN algorithm is between 0.76 and 0.81. This shows that the improved BP algorithm can realize the nondestructive detection of foreign matters in cosmetics, ensure a high accuracy and fast speed, and provide consumers with a sense of safe use of cosmetics, it can also improve consumers’ satisfaction with the use of cosmetic products. Show more

Keywords: BP algorithm, neural network, cosmetic foreign body, intelligent recognition, non-destructive testing

DOI: 10.3233/JCM-226696

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1395-1407, 2023

Authors: Shen, Wentao | Zeng, Yawen | Zhang, Weiran | Tang, Zhi | Xie, Hongping

Article Type: Research Article

Abstract: In order to respond to the national goal of “carbon neutralization” and make more rational and effective use of photovoltaic resources, combined with the actual photovoltaic substation project, a fixed adjustable photovoltaic support structure design is designed. By comparing the advantages and disadvantages of the existing support, an innovative optimization design is proposed, and the mechanical structure of the support is analyzed by ANASYS to check the rationality of the design. Saving construction materials and reducing construction costs provide a basis for the reasonable design of photovoltaic power station supports, and also provide a reference for the structural design of …fixed and adjustable supports. Show more

Keywords: Photovoltaic support design, finite element analysis, structural design, carbon neutralization

DOI: 10.3233/JCM-226647

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1409-1423, 2023

Authors: Yuan, Quan | Chang, Weipeng | Xu, Shenglin

Article Type: Research Article

Abstract: At a time when communication network technology is developing rapidly, the security of the Internet has aroused widespread concern in the academic community. In particular, electronic payment, which has been booming in recent years, has great security risks and people are prone to information leakage and property loss in the process of payment. In order to solve these problems, this study adopts the AES to encrypt the information in the payment process, introduces the RSA Public Key System (RSA) and the SM4 packet cipher algorithm for comparison, and analyses their encryption (decryption) speed, decryption (decryption) speed and encryption speed respectively. …(decryption) speed, as well as PR curve, Loss function and sensitivity. The results show that the AES algorithm has a faster encryption (decryption) speed compared to the other two algorithms. In the PR curve, the AES algorithm has an AP value of 0.9988, which is significantly higher than the other two algorithms, and has a better balance between accuracy and recall, and better performance. In the sensitivity analysis, the AES algorithm can have the highest sensitivity of 97.88%. This is significantly higher than the 93.47% and 96.59% of the other two algorithms. Moreover, as shown by the Loss function of the AES algorithm, it converges faster and the Liss value varies between 0.1 and 0.9. In summary, the AES algorithm has a faster encryption speed and is better in terms of accuracy, convergence speed and security factor in all aspects. This also demonstrates the feasibility and effectiveness of this algorithm for information security protection in electronic payment processes. Show more

Keywords: AES, Rijndael, electronic payments, encryption, Security, RSA, SM4

DOI: 10.3233/JCM-226694

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1425-1438, 2023

Authors: Liang, Fu | Wang, Longzong | Lai, Lianfeng

Article Type: Research Article

Abstract: Information technology brings popularity of the Internet, which broadens college students’ knowledge. Unexpectedly, the large amounts of information has a tremendous effect on the psychological ideology of college students who are lack of social experiences. This paper discusses how to better apply web crawler technology to analyze the potential risks of college students’ psychological crisis in the Internet environment. It is quite necessary for us to give full play to the initiative of ideological and political education in colleges and universities so as to prevent some negative and non-positive information and ideas from infiltrating and eroding students. Moreover, we should …also provide a better guidance on students’ positive energy behavior, by creating an atmosphere, formulating measures, strengthening intervention as well as other mental health education methods. Show more

Keywords: Internet, web crawler, college students, mental health education

DOI: 10.3233/JCM-226650

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1439-1450, 2023

Authors: Jia, Jun | Wang, Maofei | Dai, Yongdong | Zhang, Haoling | Gao, Song | Wang, Shenyu

Article Type: Research Article

Abstract: Operation accidents caused by deteriorated insulators occur from time to time, which poses a direct threat to the safe and stable operation of transmission lines. Much research has been done at home and abroad on the degradation mechanism of deteriorated insulators, the electric field distribution characteristics of insulator strings and the influence of deteriorated insulators on the space electric field, but there is little research on the influence of three-phase electrification on the space electric field of insulator strings. Therefore, this paper studies the simulation and detection of electric field distribution of deteriorated insulators in three-phase transmission lines. First, the …difference between three-phase electrification and single-phase electrification on the space electric field of insulator strings is simulated and analyzed, and the influence of deteriorated insulators on the space electric field distribution of insulator strings under three-phase electrification is studied. Second, based on simulation results, a detection method for deteriorated insulators in three-phase overhead trans-mission lines is proposed, and a non-contact space electric field measurement device based on Unmanned Aerial Vehicle (UAV) is developed. Finally, a Unmanned Aerial Vehicle inspection system is used to test the transmission lines in combination with an electric power department, and the simulation results and the effectiveness of the proposed detection method are verified. Results show the electric field distribution of insulator strings is obviously different between three-phase electrification and single-phase electrification, and when the detection distance is 300 mm, the proposed detection method and device can effectively identify deteriorated insulators in three-phase transmission lines. Show more

Keywords: Insulator, electric field distribution, three-phase electrification, non-contact type

DOI: 10.3233/JCM-226658

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1451-1466, 2023

Authors: Tian, Xuejun | Tian, Xinyuan | Pan, Bingqin

Article Type: Research Article

Abstract: In order to allow users to incorrectly identify images by manipulating them using deep neural networks, this paper analyses the shortcomings of deep learning for image classification. It also develops a game that uses this technique. In the game, players can select one of their preferred product categories, causing the model to classify other product categories incorrectly as the one they selected. The goal of this game is to demonstrate to players the limitations of AI. We evaluate these programs based on their overall effectiveness, user satisfaction, and achievement of their objectives. The results show that this program is a …successful method for arousing curiosity and stimulating thought. They can learn to appreciate the limitations of AI and the need to prioritize AI security in their daily activities. Show more

Keywords: Deep learning, adversarial attack, image classification, game

DOI: 10.3233/JCM-226660

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1467-1478, 2023

Authors: Tian, Huan

Article Type: Research Article

Abstract: Color is one of the three major elements of print advertising, and different color combinations can trigger different emotional experiences of human beings. At present, the application of color in advertising in China is relatively mature, but it is limited to the traditional application method and has not been combined with big data technology. From the perspective of business needs, this research analyzes the process of visual creativity from the perspective of business value-added, and analyzes the role of big data in it. Then it introduces the semantics of common colors and how to incorporate color semantics into advertising design. …And a sequence mining-based advertising click-through rate prediction model is proposed. The Criteo dataset is used as the training set. The AUC value of the model is 0.702 and the loss value is 0.415. Compared with other models, AUC values increased by 10.16%, 4.70%, 2.69% and 2.30%, respectively. Losses decreased by 10.17%, 9.19%, 6.11% and 7.57%, respectively. Finally, the online shopping data of 20 consumers was used as the test set to predict their color preferences, and the prediction accuracy was about 70%. Among them, the prediction accuracy of the group with stable shopping habits was 72.76%, and that of the group who liked to try new things was 70.60%, both meeting the expectation. Through experiments, it is concluded that the model has good performance and stability, and can more accurately judge consumers’ consumption preferences. Show more

Keywords: Big data, visual communication, color semantics, sequence mining, advertisement click-through rate

DOI: 10.3233/JCM-226700

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1479-1490, 2023

Authors: Li, Kai | Zhu, Rui | Wang, Zhenguo | Zhou, Xiaoyu | Wang, Mingxin | Xu, Siyu | Gong, Yicheng

Article Type: Research Article

Abstract: The structure of the long-span transmission tower is a typical nonlinear structure with the characteristics of great height, large line span, heavy overall weight and flexible tower body. The current design code only analyzes the traditional tower types, but the analysis of the truss structure of transmission tower is limited. Aiming at improving the design defects of the structure of long-span transmission towers, this paper uses the finite element software APDL to build the three-dimensional finite element model of a long-span transmission tower, to carry out the modal finite element analysis as well as to extract the specific parameters of …each modal finite element mode: Modality, Natural frequency of vibration, Periodicity. The results show that the natural vibration period of the main machinery of this type of steel transmission tower is about 0.37–1.37 s; The structure of the long-span transmission tower has certain displacements in six degrees of freedom, in which the value of the X-dimensional displacement is the largest. There are some large displacements and local torsion in the high-order mode, combined with the results of modal analysis, so it is suggested to consider the structural improvement or external reinforcement of the weak parts of the long-span transmission tower. Show more

Keywords: Long-span transmission tower, modeling, modal analysis, APDL

DOI: 10.3233/JCM-226644

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1491-1501, 2023

Authors: Chen, Chen

Article Type: Research Article

Abstract: The layout and design of ecological landscaping is an important part of the construction and development of modern cities. In the 3D reconstruction of the spatial pattern of the light and shadow interlaced zone of the ecological landscape, the complexity and particularity of the ecological landscape structure make it difficult for the three-dimensional reconstruction stereo matching set to meet the accuracy requirements, and the quality 3D image construction cannot meet the requirements of landscape planning. Based on the principle of binocular stereo vision, a regional feature stereo matching algorithm (rsurf) is used to improve the accuracy of feature matching. Considering …that the algorithm is easy to filter out the detailed features of the image, the improved RANSAC algorithm is used to filter the matching results. The experimental results show that in the matching cost test of the optimal matching window, the 15 × window neighborhood has the lowest matching cost, and the generated value in the 100 × 100 source window is 0.824. In the test after matching and fusion, the rsurf algorithm is superior to the surf algorithm in both RMS and PMS error performance, and can better meet the requirements of 3D reconstruction of the binocular vision system. The research content has an important reference for the application of landscape visualization 3D technology, and improves the overall layout effect of landscape landscape. Show more

Keywords: Ecological garden landscape, criss-cross area, spatial pattern, improved RANSAC algorithm, stereo matching

DOI: 10.3233/JCM-226712

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1503-1516, 2023

Authors: Liu, Hongliang | Gao, Shuguo | Sun, Lu | Tian, Yuan

Article Type: Research Article

Abstract: During the transformer winding deformation process, the leakage magnetic field around the winding will change accordingly. Therefore, it is an effective method to monitor and track the change of the leakage magnetic field and then analyze and judge the state of the transformer. This paper firstly uses Comsol Multiphysics software to establish a 110 kV transformer electromagnetic simulation calculation model. Based on the simulation results of magnetic leakage distribution, an installation plan for the internal magnetic leakage sensor of a 110 kV true transformer is determined. The measurement results of the true single short-circuit test under different working conditions verify …the accuracy of the simulation model. Subsequently, a number of B-phase high-centered three-phase short circuit (H-M B) true type tests were carried out, and the relationship between the magnetic leakage distribution characteristics and the impedance change rate after each impact was analyzed. The results show that before the transformer is seriously deformed due to multiple short circuit shocks, the sensitivity of the impedance change rate to the winding deformation is low, and the first five shocks only increase from 0.11% to 0.39%. However, the difference ratio between the simulation value and the test value of magnetic flux leakage (MFL) has obvious changes in each small deformation. BX3 increases from 1.77% to 5.62%, and BX4 increases from 2.08% to 6.55%. The difference ratio of four shocks before winding deformation is more than 6%. Therefore, by monitoring the flux leakage magnetic induction intensity, when the difference ratio is greater than 6%, strengthen the vigilance, which can provide a certain basis for winding monitoring before serious deformation. Show more

Keywords: Transformer, comsol, magnetic leakage sensor, magnetic flux leakage intensity, deformation monitoring

DOI: 10.3233/JCM-226656

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1517-1528, 2023

Authors: Zhang, Xin | Li, Yanhong | Song, Qiuxuan

Article Type: Research Article

Abstract: Many scholars have utilized Bodalal’s mathematical model in the development of environmentally friendly building materials to describe the physical diffusion process of volatile organic compounds. In the model, the key to calculating the diffusion coefficient of volatile organic compounds in building materials is the value of the auxiliary parameter α 1 and q . This paper improves the method of solving auxiliary parameter values by using extreme value theory. Several other calculation methods are also presented. The process of solving it is explained in detail, and an example is used to verify its accuracy. …As these methods are very easy to learn and easy to implement on a computer, they can greatly reduce error rates, which makes them popular and useful. Show more

Keywords: VOCS, the diffusion coefficient, extremum theory, calculation method

DOI: 10.3233/JCM-226665

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1529-1536, 2023

Authors: Zhang, Xuejun | Zhang, Susu | Bu, Zhaohui | Ma, Liangdi | Huang, Ju

Article Type: Research Article

Abstract: Breast cancer is the most frequent cancer and the leading cause of death among females. Diagnosis mass from mammogram correctly can reduce the unnecessary biopsy to a large extent. In this paper, we present a novel mammogram classification method combining the Random Forest and the Locally Linear Embedding (LLE) dimensionality reduction algorithm for texture features. The proposed method consists of three stages. In the first stage, preprocessing is performed to enhance the contrast and suppress the noise of the ROI images. Then, the sixteen-dimensional texture features are extracted from Grey Level Co-occurrence Matrix (GLCM) as the input dataset of LLE …and being mapped into a five-dimensional subspace. Finally, a Random Forest classifier is investigated for the mammogram classification and compared with the other four classifiers (SVM, KNN, Logistic Regression, MLPC). The experimental results show that the Random Forest classifier outperforms than the others, with an average accuracy of 92.87% and the AUC value of 0.99, that indicates that the combination of LLE algorithm and Random Forest classifier is a promising method for the mammogram classification. Show more

Keywords: Mammogram, GLCM, texture analysis, Random Forest classifier, LLE

DOI: 10.3233/JCM-226669

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1537-1545, 2023

Authors: Li, Zhihui | Si, Yiyi | Zhu, Yuhua

Article Type: Research Article

Abstract: When using the support vector regression method to predict grain storage temperature, it is challenging to choose the appropriate model parameters. Generally, it is effective to examine the trend of grain storage temperature in different layers after ventilation intervention. To enhance the performance of a support vector machine, it is necessary to choose an appropriate parameter optimization algorithm. The adaptive particle swarm optimization algorithm completes the operation by continuously updating the particles in the spatial domain; after discussing its application principle in detail, the convergence effect is more optimal; and the algorithms are applied to parameter optimization for support vector …regression models. After employing the adaptive particle swarm optimization algorithm, the evaluation indicators and experimental prediction results demonstrate that the APSO model has fewer errors, a higher tracking degree, superior generalization performance, and greater prediction accuracy. This is a useful resource for forecasting grain temperature trends. Show more

Keywords: Grain temperature prediction, adaptive particle swarm optimization, support vector regression

DOI: 10.3233/JCM-226642

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1547-1559, 2023

Authors: Hu, Jianhua | Wang, Bo | Liu, Xiaolin | Zheng, Shuzhao | Chen, Zongren | Wu, Weimei | Guo, Jianding | Huang, Woqing

Article Type: Research Article

Abstract: With the rapid growth of Internet video image information, there is a large amount of redundancy in image data. Use less data stream information to transfer the image or the amount of information contained in the image. Its purpose is to reduce the redundancy of images, so as to store them at low bit rate and reduce the data storage space. In the general image compression method, the hybrid coding framework is adopted. Each algorithm adopts a fixed algorithm mode through a specific design algorithm, without global optimization. Image compression is mainly divided into prediction, transformation, quantization, digital entropy coding …and other steps. At present, there are many researches on super-resolution network based on deep learning technology. The main function is to reconstruct high-resolution image replace image magnification low-resolution images such as linear interpolation, which has a great performance improvement image resolution, noise reduction, deblurring and so on, but there is no effective way to use super-resolution network applications to improve quality of compression reconstructed image quality. This paper involves a new method that using image super-resolution residual learning network to improve quality of compression image, our method, the reduced image is encoded into a content stream and a transmission corresponding parameter is encoded into a model stream. Firstly, the original image is scaled down 1/2 size of source image, then encode the small image into content stream with the existing codec. Secondly, the residual learning super-resolution (SR) network is used for image filtering to scale up reconstructed image with decode image resizing method and boost the quality of edge feature extraction of image. Our results show that there is significant performance improvement of h265 in low resolution reconstructed image (bits-per-pixel less than 0.1). Show more

Keywords: Image compression, convolutional neural network, image super-resolution network

DOI: 10.3233/JCM-226653

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1561-1571, 2023

Authors: Qi, Wei | Xu, Yiting | Gao, Zongqian | Xu, Zhiou | Huang, Zhenzhen | Xiao, Shuo

Article Type: Research Article

Abstract: Most nodes in wireless sensor networks (WSNs) are battery powered. However, battery replacement is inconvenient, which severely limits the application field of the networks. In addition, the energy consumption of nodes is not balanced in WSNs, nodes with low energy will seriously affect data transmission capability. To solve these problems, we utilize mobile chargers (MCs) in WSNs, which can move by itself and charge low-energy nodes. Firstly, we construct a mixed integer linear programming model (MILP) to solve maximum flow problem, which is proved to be NP-hard problem. To maximize flow to the sink nodes, the BottleNeck algorithm is used …to generate the initial population for the genetic algorithm. This algorithm takes path as the unit and schedules MCs to charge the lowest energy node first. Then, the improved adaptive genetic algorithm (IAGA) is utilized to simulate the natural evolution process and search for the optimal deployment location for MCs. The experiment results show that IAGA can effectively improve the maximum flow of sink node compared with other methods. Show more

Keywords: Wireless charging, mobile chargers, wireless sensor networks, schedule MCs

DOI: 10.3233/JCM-226667

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1573-1587, 2023

Authors: Hu, Yihua | Zhang, Shulin | Chen, Yanhui

Article Type: Research Article

Abstract: Robots are widely used in all walks of life, and their excellent work efficiency has been paid attention to. As the key component of robot, manipulator plays an important role in the running performance of robot. In order to effectively improve the trajectory accuracy and efficiency of the manipulator, a six degree of freedom (6-DOF) modular manipulator trajectory planning method based on polynomial interpolation is proposed, and its feasibility and effectiveness are verified by experiments. At the same time, the performance of the method is compared with two other methods of the same type. The experimental results show that the …six degree of freedom modular trajectory planning method has a shorter running time, and the shortest running time is 1.62 s. Compared with the directions in previous studies, the planning trajectory of the proposed method is more practical and its accuracy is higher. In the iterative process, the running time of the proposed method is also the shortest. In addition, the minimum error of the three methods is about 1%, which is lower than the other two methods. It is concluded that the six degree of freedom modular trajectory planning method has high feasibility and performance, which is of great significance to improve the operating efficiency and stability of the robot. Show more

Keywords: Polynomial interpolation, six degrees of freedom, manipulator, trajectory planning

DOI: 10.3233/JCM-226672

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1589-1600, 2023

Authors: Li, Cong

Article Type: Research Article

Abstract: In order to improve the recognition effect of laser images, this study designed an intelligent recognition method of laser images based on big data analysis technology. On the basis of setting up the laser holographic scanning device and parameters, the laser image is obtained by using the calibration method of vision system. In order to avoid the limitation of coordinate system in the process of laser image recognition, a rational function model with general attributes is constructed. Then, convolutional neural network is used to output the feature data of laser images, and Spark parallel support vector machine algorithm is used …to complete the classification of laser images. Finally, the SVM classification model based on the big data analysis technology is constructed. The texture feature data can be input to quickly output the classification results of laser images, and then the intelligent classification and recognition of laser images can be realized according to the probability distribution. Experimental results show that this method can accurately identify the tiny features in laser images, and the recognition results have high peak signal-to-noise ratio and high recognition accuracy. Show more

Keywords: Laser holographic scanning, visual calibration, laser image, texture features, image classification, probability distribution, support vector machine, rational function model

DOI: 10.3233/JCM-226674

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1601-1615, 2023

Authors: Zhang, Lan | Zhu, Chunyan | Liu, Jialin | Bai, Xue

Article Type: Research Article

Abstract: One of the largest water consumers among public institutions, hospitals are characterized by water usage for various functions. Therefore, the nuanced water use requires a special methodology to determine the hospital water conservation efficiency. Based on the method of “water consumption-influencing factors in the base period”, we constructed a model for calculating the water savings amount at hospitals and demonstrated its applicability by exploring two case studies. The proposed method can help hospitals to accurately calculate the amount of water savings and determine their water conservation potential, thus evaluating the effects of the implemented water conservation measures, and achieving their …targets. Show more

Keywords: Hospital water use, water conservation, water savings calculation method, water efficiency

DOI: 10.3233/JCM-226677

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1617-1623, 2023

Authors: Zhang, Nan | Zheng, Xiaojing

Article Type: Research Article

Abstract: The work of traditional intangible cultural heritage analyzes the intangible cultural works in restricted scales way. So, it is difficult to multi-scale understand the closely related to intangible cultural heritage. In this paper, visual analytics approaches are proposed for the preserve and protection those historic cultural heritages, which include multi-dimensional visualization, temporal visualization, and geospatial visualization. We take national intangible cultural heritage in Heilongjiang province as an example. Through visual analysis of intangible cultural heritage in Heilongjiang province, experts can form multi-dimensional understanding the culture of Heilongjiang province, including the categories, numbers and distributions. Furthermore, those methods we proposed can …effective help experts make an in-depth analysis of those intangible cultural heritage, and provide them a new insight in a comparative way. Show more

Keywords: Intangible cultural heritage, visual analytics, Heilongjiang province

DOI: 10.3233/JCM-226679

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1625-1633, 2023

Authors: Fan, Wenguang

Article Type: Research Article

Abstract: Engineering investment is the basic investment of the whole national economic development. When the project investor obtains its expected return, it may have other beneficial benefits for social organizations or people outside the subject, but the investor cannot obtain such benefits. Spillover usually occurs from three aspects: economy, technology and knowledge. The spillover effect of project investment usually brings obvious spillover effect, which has positive benefits to society, but may also produce unfavorable factors. Therefore, it is necessary to predict the project investment spillover. When it is predicted that the investment spillover will have more favorable benefits, the preparation of …relevant investment funds can be started, and when it is predicted that there will be unfavorable spillover benefits, the investment in related engineering projects will be terminated. Project investment spillover effects usually have specific rules. On the basis of summarizing and analyzing historical project investment spillover effects, the specific situation of its spillover effects can be obtained, and then the rules can be learned in combination with specific algorithms to complete the project investment spillover effects. predict. The purpose of this paper is to provide investors and institutions with a valuable investment forecasting reference method, combined with the relevant theories of the investment value of engineering market-oriented enterprises, using quantitative analysis methods and quantitative analysis methods, so as to provide an investment based on data and algorithms. The spillover value forecast method supports and promotes the development and construction of national key projects. Based on the completion of the entire prediction model, this paper uses the particle swarm optimization method of the deep neural network model process studied in this paper, and based on the relevant data of 284 historical engineering investment overflow cases, the algorithm is trained and output, and then the investment overflow of each project is obtained. The relative score of the predictions, and analyzing this overflow prediction. Through the obtained comprehensive prediction score and according to the result analysis. Corresponding conclusions and future development directions are put forward to provide theoretical guidance for investors and institutions to invest in investment direction and estimate investment spillover effects. Show more

Keywords: Engineering investment, deep neural network model, particle swarm optimization, prediction

DOI: 10.3233/JCM-226678

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1635-1650, 2023

Authors: Lei, Xuetang | Xie, Yaya | Lei, Jinkai

Article Type: Research Article

Abstract: In the rough signal processing of AC intelligent sensor, the effective value and initial phase of voltage/current determine the test accuracy. To improve the harmonic detection and compensation performance of the existing APF and promote the improvement of power grid power quality. The direct positioning method is used as the comparison method, and the error LMS method is proposed to obtain and test the voltage and current signals of intelligent sensors. The simulation results of error LMS method show that the accuracy of voltage RMS and initial phase value calculated by method 1 increases with the increase of the number …of sampling points, while the accuracy of voltage RMS of method 2 and method 3 does not change significantly. The results of correlation analysis method show that the test accuracy of the proposed method is 1/2–1/3 of the direct definition method when the amplitude of interference noise signal is 5%, 10% and 15%. Compared with the direct definition method, the rough signal processing technology has lower sampling amount and higher test accuracy, which helps to simplify the system and save the overhead cost. Show more

Keywords: Intelligent sensor, minimum mean error method, correlation analysis method, signal processing, testing

DOI: 10.3233/JCM-226686

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1651-1665, 2023

Authors: Wang, Yichen | Zhang, Pei | Wang, Yi

Article Type: Research Article

Abstract: Human posture detection is easily affected by the external environment, resulting in blurred results of limb feature extraction. In order to improve the accuracy and speed of human motion detection, this paper proposes a deep learning-based motion detection method in competitive sports training. The double parallel convolution network algorithm in the depth learning algorithm is used to process the collected action information, extract the body action features, and greatly reduce the operation scale; With the help of the theory of motion mechanics, the mechanical parameters in the motion process are calculated to eliminate outliers and reduce feature dimensions; With the …help of motion inertial sensors and joint degrees of freedom, the limb motion detection results are obtained. The experimental results show that the average recognition rate of the method for different motion actions is 99.5%, and the average detection time is 148 ms, with good application performance. Show more

Keywords: Deep learning, convolutional neural network, body motion recognition, kinematic mechanics theory, joint degrees of freedom, inertial sensor

DOI: 10.3233/JCM-226688

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1667-1678, 2023

Authors: Jia, Faxian

Article Type: Research Article

Abstract: The modern network social mode accelerates the interaction of data. Under the background of the continuous development of big data and artificial intelligence technology, the ability to collect and process data has become one of the core competitiveness of enterprises. A good data management mode can also help enterprises to achieve more information resources, and win more opportunities in the industry competition, so as to obtain more benefits. The standard definition of big data by scholars in recent years is to search and make decisions based on massive data sets, and the data that can be used for analysis is …the internal data of big data. The key to big data is not the massive data set, but the method to analyze the data. At present, big data has penetrated into the development and analysis of all industries, for example, the medical industry records the personal diagnostic data of patients with different diseases. Through comparative analysis and decision-making with the diagnostic data of other historical cases, a third-party reference is provided for the treatment of current patients, thereby avoiding misjudgment and misdiagnosis. With the rapid development of electronic components and data science and technology, IoT technology has gradually entered the lives of citizens. The concept of the Internet of Everything is no longer an empty talk. Smart homes have become a must-have smart device for most homes. Other similar smart cities, smart communities, and smart building designs have also begun to adopt IoT technology, and enterprise management and monitoring have also followed the trend. Connect with IoT technology. If an enterprise wants to gain a firm foothold in the industry, it not only needs excellent manufacturing level, but also needs to carry out effective cost management, and manage costs in a more scientific way, which can gain advantages for the company’s product prices. Because if the cost management of the enterprise is successful, it can reduce unnecessary waste of funds when the enterprise produces products, thereby driving the overall operating income of the enterprise. Through big data and Internet of Things technology, it can help in all aspects of enterprise management. Combining with the management dilemma of BYD in the era of big data, this paper proposes an enterprise management and monitoring method that combines big data and Internet of Things technology, business opportunity acquisition, business quality monitoring and other aspects have greatly improved. Show more

Keywords: Big data, Internet of Things, enterprise management

DOI: 10.3233/JCM-226684

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1679-1690, 2023

Authors: Zhang, Weiwei

Article Type: Research Article

Abstract: In the intelligent age, computers are required to help people complete simple daily work. Among them, computer voice databases and systems occupy a very important position in the field due to their wide application. In order to optimize the system design method, the application of IGA algorithm is proposed, and the performance of the model under the algorithm is compared and tested. The algorithm experiment shows that when the IGA objective function value is 34.4, there is no change, and the number of iterations is 100; Compared with the traditional genetic algorithm, the value of the optimal solution is always …the minimum. Then the error of the optimal solution under different algorithms is compared and analyzed. It is found that the error of the optimal solution under IGA operation has the minimum value of 0.0079; The experiment of speech recognition efficiency shows that the speech recognition rate under the intervention of IGA algorithm has increased by 8%, and the overall efficiency is higher than 95%. It can be seen from the above results that IGA is helpful to the acquisition of voice database data, and improves the recognition efficiency. The feasibility of the method is high, which is of great significance to the development of China’s intelligent system industry. But at present, the overall progress of the voice system is still limited, so expanding research methods to apply to the field of voice system is still the next research direction that can be explored. Show more

Keywords: Improved genetic algorithm, speech data system, computer database, speech recognition rate

DOI: 10.3233/JCM-226698

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1691-1703, 2023

Authors: Xia, Fang | Chu, Shiwei | Liu, Xiangguo | Li, Guodong

Article Type: Research Article

Abstract: With the rapid development of hyperspectral image technology, remote sensing technology has ushered in an innovation in theory and application, and hyperspectral remote sensing images have come into being. However, due to its high data dimensionality, it is difficult for statistical classifiers to work on it, making the technology face development difficulties. Therefore, how to effectively reduce the dimensionality of hyperspectral remote sensing images has gradually become a research hotspot in this field. The study clusters bands by K-means algorithm, and then combines the least mean square algorithm in adaptive filtering and recursive least squares method, and uses this as …the basis for band selection. Finally, the dimension reduction effect is verified. The experimental results show that the improved band selection method achieves an overall accuracy of over 80% and 90% in the hyperspectral datasets of Pavia University and Idian Pine respectively, with the Kappa coefficient reaching 0.9. In the overall dimensionality reduction classification of the Indianan data, the accuracy also reaches 90% and can be maintained consistently, indicating that the method has high accuracy and can effectively reduce the dimensionality of hyperspectral remote sensing images. Show more

Keywords: Adaptive filtering, minimum mean algorithm, K-means, hyperspectral remote sensing, image dimensionality reduction

DOI: 10.3233/JCM-226714

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1705-1717, 2023

Authors: Yang, Yafei | Wang, Guoqiang | Wang, Li | Chen, Yinsheng | Shen, Zhizheng

Article Type: Research Article

Abstract: In this experiment, the linear CCD mixing concentration online detection device was studied under five concentrations of carmine solution: 0.1 g/L, 0.3 g/L, 0.5 g/L, 0.7 g/L, and 0.9 g/L, for the factors that can affect the detection accuracy in the real spraying process (spray flow rate, spray pressure, liquid temperature, and light intensity). The results show the following results: different spray flow rates have less influence on the concentration detection results; the greater the concentration of the solution, the less the influence of the spray pressure on the detection; the smaller the concentration of the solution, the greater the …influence of the spray pressure on the detection; the greater the concentration of the solution, the greater the influence of the liquid temperature on the detection; the smaller the concentration of the solution, the greater the influence of the liquid temperature on the detection; the smaller the concentration of the solution, the greater the influence of the liquid less. Show more

Keywords: Drug mixing concentration, online detection, CCD, concentration detection, the average effective gray

DOI: 10.3233/JCM-226670

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1719-1730, 2023