Journal of Computational Methods in Sciences and Engineering - Volume 22, issue 4

Authors: Liu, Gaochuan | Shan, Weifeng | Chen, Jun | Che, Mengqi | Teng, Yuntian | Huang, Yongming

Article Type: Research Article

Abstract: Geomagnetic interference events seriously affect normal analysis of geomagnetic observation data, and the existing manual identification methods are inefficient. Based on the data of China Geomagnetic Observation Network from 2010 to 2020, a sample data set including high voltage direct current transmission (HVDC) interference events, other interference events and normal events is constructed. By introducing machine learning algorithms, three geomagnetic interference event recognition models GIEC-SVM, GIEC-MLP, GIEC-CNN are designed based on support vector machines (SVM), multi-layer perceptron (MLP) and convolutional neural networks (CNN) respectively. The classification accuracy for each model on the test set reached 76.77%, 84.96% and 94.00%. Two …optimal GIEC-MLP and GIEC-CNN are selected and applied to the identification of geomagnetic interference events at stations not participated in training and testing from January, 2019 to June, 2021. The accuracy are 72.11% and 78.24% respectively, while the efficiency is 150 times that of manual identification. It shows that the geomagnetic interference event recognition algorithm based on machine learning algorithm has high recognition accuracy and strong generalization ability, especially the CNN algorithm. Show more

Keywords: Geomagnetic interference, automatic recognition, machine learning, HVDC, CNN

DOI: 10.3233/JCM-226015

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1157-1170, 2022

Authors: Zhu, Qi-Wen | Gu, Bin | Ji, Liang | Sun, Dong | Liu, Yu-Dong | Yu, Bao-Ming

Article Type: Research Article

Abstract: The body-temperature is the most significant vital signs of human and animals. It is easily imaginable that measurement of body-temperature of animals will be much more difficult than that of human being due to lack of endurance or fear of measuring instrument. Infrared temperature measurement device may be a solution, however coverage of hair and fur may incur a large error. To address this issue, a rapidly executed algorithm is developed for prediction of steady state body temperature, which needs only a few one-tenth of measurement duration that the currently popular machine learning-based approach usually requires. Let a cubic function …c ⁢ ( t ) fit the sampled temperature data which are generated by the measurement within a significantly short duration from t n - k to t n , k > 0 . Then let a quadratic function f ⁢ ( t ) = a 2 ⁢ t 2 + a 2 ⁢ t + a as a prediction function go through the point (t n , c ⁢ ( t n ) ) and share the same slope of s n thereat. Finally try to find a next point (t n + m , f ⁢ ( t n + m ) ), m > 0 , where the slope satisfies s n + m = s n / 2 and m depends strongly on s n through an empirical formula. Accordingly, f ⁢ ( t ) can be determined by (t n , c ⁢ ( t n ) ), s n and s n + m . Experiments indicate that the maximum of f ⁢ ( t ) approaches well the steady state temperature of the measured subject with a quite small error. Show more

Keywords: Body-temperature, prediction, fitting

DOI: 10.3233/JCM-226018

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1171-1177, 2022

Authors: Zheng, Lu | Ko, Young Chun

Article Type: Research Article

Abstract: In order to solve the problems of high computational complexity, poor dimensionality reduction, and reduced clustering effect when the clustering task faces a large amount of big data, the application of a large data adaptive semi-supervised clustering method based on deep learning is proposed. Through the self-encoder of the deep clustering network, the analysis of the confrontation network is generated, and the semi-supervised deep clustering algorithm and algorithm of the adaptive strategy are optimized. Through the encoder layer structure of the deep coding network, different parameters are set for all data sets for algorithm experimental analysis. The results show that …the data obtained by this method is faster, more accurate and more optimized than the traditional clustering method, which proves the effectiveness of the method. Show more

Keywords: Big data, deep learning, semi-supervised, learning application

DOI: 10.3233/JCM-226019

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1179-1193, 2022

Authors: Lu, Chunhua | Wang, Xuan | Nie, Liming | Bao, Wenjie | Huang, Xiaodong | Yang, Fan | Wang, Bo | Huang, Chengpeng

Article Type: Research Article

Abstract: With the continuous update and iteration of Internet information technology, the application of BIM (Building Information Modeling) technology in the fields of project management, cost and construction is becoming more and more popular. The field of project cost relies on the significant advantages of BIM technology to realize the intelligence of project cost management. It can effectively promote the horizontal information collection and vertical information interaction of different participants, and achieve a good information exchange and interaction effect. This paper combines the characteristics of China nuclear power engineering projects, applies building information modeling (BIM) technology, and integrates it into the …nuclear power engineering cost software framework. This paper firstly analyzes the basic characteristics of China nuclear power engineering cost software, and puts forward the key functional requirements for existing cost software. On this basis, the basic characteristics of foreign mainstream construction cost software with BIM technology and the feasibility of its application in China is also analyzed. The model consists of two parts, namely the BIM data management platform and the functional model of the construction project budget subsystem. Among them, the BIM data management platform realizes the analysis, storage and management of IFC (Industry Foundation Class) data, and provides a user interface for specific professional fields, such as the field of construction engineering budget, while the construction engineering budget subsystem provides users with cost budgeting expertise. In addition, this paper describes in detail the method of using BIM technology to create the most used pipe network model in cost assessment. Based on Revit software, combined with the use of visual programming tools Dynamo and Revit API, the repetitive and tedious manual modeling process is automated to compete the creation of the BIM model of a large number of pipe networks in a relatively short time, and make the model carry rich engineering information. This paper establishes a basic framework suitable for China nuclear power engineering cost software, which can lay the foundation for the subsequent development of corresponding software. The pipeline network BIM establishment method proposed in this paper can greatly improve the work efficiency of traditional CAD modeling, realize seamless connection with cost assessment, and has broad engineering application prospects. Show more

Keywords: BIM, nuclear power project cost, cost analysis software

DOI: 10.3233/JCM226023

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1195-1207, 2022

Authors: Zhang, Fujian | Ye, Weidong | Lei, Guoping | Liu, Yingying | Wang, Xian

Article Type: Research Article

Abstract: The power battery is a key component of the electric vehicle, and its State of health (SOH) parameters directly affect the safety and reliability of the electric vehicle. Considering the problem of the reduced SOH estimation accuracy of Li-ion battery, this paper proposes a joint algorithm of the firefly algorithm-back propagation neural network K-means (FA-BPNN-K-means) for SOH estimation to alleviate the wide voltage platform and severe polarization. In particular, the BPNN model of the battery is first established. The ohmic resistance, polarization resistance, and polarization capacitance of the battery are used as the input parameters of the model, and SOH …was used as the output parameters. Secondly, the firefly algorithm (FA) is used to optimize BPNN for SOH estimation of Li-ion battery, solving the problem that BPNN is easy to fall into the local minimum and the convergence rate is slow. Finally, the predicted output of the FA-BPNN model is substituted into the K-means algorithm for clustering, and the data points for evaluation are obtained to reduce the cumulative error caused by the battery model. Compared with the BPNN algorithm, FA-BPNN-K-means joint optimization algorithm, obtaining lower error in SOH estimation, and it has good convergence. Besides, it is accompanied by higher prediction accuracy, which can guarantee the stable operation of the battery management system. Show more

Keywords: Firefly algorithm (FA), Li-ion battery, back propagation neural network (BPNN), K-means algorithm, State of health (SOH)

DOI: 10.3233/JCM226028

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1209-1222, 2022

Authors: Qi, Lin | Pei, Yulong | Dong, Jun

Article Type: Research Article

Abstract: This paper proposes a collaborative optimization method for transportation planning and land use. This method combines system dynamics models, structural equations, DEA evaluation and BP neural network technology to construct a complete transportation planning and land use collaborative optimization system. In this system, system unit determination is a key problem, which has a different relationship with each stage. This paper uses the DEMATEL model to construct a causality diagram and an incidence matrix for the system units, to identify the central influencing unit and causal influencing unit of the method of collaborative optimization of transportation planning and land use. While …simplifying the model through the DEMATEL model, the macro interaction mechanism between urban traffic and land use will be clarified. Further, the extracted key influence units can be micro-decomposed to construct subsystems of micro-elements, which makes preliminary preparation for the analysis of static and dynamic integration model. Show more

Keywords: Transportation planning, land use, system unit, DEMATEL

DOI: 10.3233/JCM226032

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1223-1233, 2022

Authors: Zhao, Yilin | Jiang, Xiaoyan | Li, Xiaobing | Gao, Pan | Shao, Yanglu

Article Type: Research Article

Abstract: Centralized photovoltaic power station is an important part of building a new power system, whose power generation unit is the main equipment of the photovoltaic power station. Therefore, it is the basis of analyzing the harmonic characteristics of photovoltaic power generation to study the harmonic generation mechanism and influencing factors of power generation units and establish the harmonic equivalent model of photovoltaic power generation units. In this paper, firstly, the harmonic generation mechanism is analyzed from the aspects of sinusoidal pulse width modulation (SPWM) and dead time of inverter. Secondly, the correlation analysis of influencing factors of output power of …photovoltaic power generation unit is carried out, and then the influence of output power on harmonics is analyzed. Thirdly, the harmonic characteristic model of photovoltaic power generation unit based on actual photovoltaic power station and influencing factors is constructed. Finally, the theoretical simulation of SPWM modulation and dead time is verified and analyzed, and the simulation results of harmonic characteristics are compared with the measured data. The results show that the harmonic characteristic of the centralized photovoltaic power station is mainly to generate high-frequency odd-order harmonics, which will generate extra high-frequency even-order harmonics when the irradiation is too high or too low, and cause interharmonics when the irradiance fluctuates on the DC side of the inverter. Show more

Keywords: Photovoltaic power generation, correlation analysis, SPWM, dead time, harmonic characteristic

DOI: 10.3233/JCM226035

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1235-1250, 2022

Authors: Du, Peng

Article Type: Research Article

Abstract: The traditional numerical analysis method of deformation mechanics of bolt support has the problems of poor numerical simulation effect and accuracy. In this paper, the numerical simulation of deformation mechanics of bolt support in high stress mine roadway is studied. This paper analyzes the principle of bolt in high stress mine roadway, constructs the deformation concentration parameter model of bolt support in high stress mine roadway, and calculates the bearing capacity of bolt; The elastic deformation equation of bolt support in high stress mine roadway is obtained, the energy balance control of bolt support in high stress mine roadway is …realized, and the numerical simulation of deformation mechanical characteristics of bolt support in roadway is realized. The experimental results show that when the impact time is 18 ms, the deformation force of the proposed method and the actual bolt support is 286 kn, which indicates that the proposed method can obtain the deformation force results of the bolt support, and the proposed method can accurately simulate the deformation mechanical characteristics of the bolt support. Show more

Keywords: Support deformation, mechanical properties, deformation lumped parameter model, elastic deformation equation

DOI: 10.3233/JCM226042

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1251-1261, 2022

Authors: Jiao, Hongtao | Wei, Baoli

Article Type: Research Article

Abstract: The current speed control methods of mineral hoisting and conveying machinery ignore the fuzzy steps of the PID control model, and the AC commutation effect of mineral hoisting and conveying machinery is poor, resulting in long delay and low accuracy of speed control. To this end, a speed control method for lifting and transporting machinery based on single neuron PID is proposed. The structure of a single neural adaptive PID speed controller is designed. A learning algorithm is introduced to optimize the AC commutation effect of the hoisting and conveying mechanical circuit. A single neuron PID controller is used to …fuzzy process the input signal to form a fuzzy language set. The speed controller port is defined, and the single neuron PID control rule is designed. Using the reduction ratio of the three-phase motor speed governor, the maximum speed required for conveying minerals is calculated, and the speed control of the mineral hoisting and transporting machinery is realized. The experimental results show that the mineral lifting deviation is small, the speed regulation time is less than 4 s, the average control delay is 200 ms, and the maximum speed regulation accuracy is 99.9%. The method in this paper has certain application value and is worthy of promotion. Show more

Keywords: Single neuron, PID controller, mineral lifting, transportation machinery, speed control

DOI: 10.3233/JCM226044

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1263-1275, 2022

Authors: Sun, Qimeng

Article Type: Research Article

Abstract: After entering the new millennium, the computing capacity of information terminal has shown a rapid development. This progress has caused cross generational changes in various fields, especially in the field of communication technology, which directly spawns a new field. Compared with the development speed of information terminal, the development of communication technology is always in the position of “catch-up”, and the main work performer is the traditional data form. This backward leads to the primitive evaluation of Ideological and political education. This paper mainly studies the application of improved machine learning algorithm and voice technology in the teaching evaluation of …Ideological and political education. The weighted naive Bayesian algorithm is applied to the teaching evaluation of Ideological and political education creatively. By inference of hypothesis model, the intervention curve of various conditions on the evaluation results is verified. The influence of class attribute probability on condition assignment is obtained, and it is used as a calculation tool for our evaluation of Ideological and political education teaching. The experimental results show that the improved weighted naive Bayesian algorithm can better integrate the speech technology and improve the evaluation accuracy. Show more

Keywords: Teaching evaluation, machine learning algorithm, data mining, weighted naive Bayesian

DOI: 10.3233/JCM226047

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 4, pp. 1277-1285, 2022