Journal of Computational Methods in Sciences and Engineering - Volume 23, issue 2

Article Type: Other

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 571-571, 2023

Authors: Cheng, Bojing | Ji, Haonan | Wang, Ying

Article Type: Research Article

Abstract: High definition map is a map used for automatic driving. Its absolute precision is sub meter level, that is, the error between the position of an element on the map and the position of the element in the real world is less than 100 cm. In addition, compared with ordinary maps, high definition maps contain more geographic information, such as road width, slope, curvature, etc. At present, high definition roads map construction is largely for the main traffic road. However, there are few studies on the construction of high definition forest roads map for forestry production and management. Thus, it …is imperative and helpful to explore an efficient and low-cost method for constructing high definition forest roads map that can provide accurate basic map services for forestry management activities. In this study, firstly, the DJI Phantom 4 RTK UAV was used for aerial photography to obtain the forest oblique images. Then, combined with close range photogrammetry, the high-resolution images under the forest are acquired and generated into dense point cloud images. Next, the two images are fused using iterative closest point (ICP) algorithm combined with manual registration; Finally, the fine-grained 3D scene model is generated by using the Context Capture 3D modeling software, based on which a high definition forest roads map was constructed using human-computer interaction model. Taking Menggongshan Forest Farm as an example, the construction of the fine 3D scene model was carried out to solve the problem of loopholes and ambiguities of the road model under forest, based on which the high definition forest roads map was constructed. To evaluate the accuracy of the forest roads map, the accuracy check was conducted. The results showed that the point position on the forest roads map, compared to the actual point, had a medium, minimum and maximum error of 0.076 m, 0.020 m and 0.170 m in plane, respectively, a medium, minimum and maximum error of 0.122 m, 0.005 m and - 0.214 m in elevation, respectively. The accuracy of the high definition forest roads map meets the need of forestry production and management activities. It is feasible to adopt the method of UAV oblique photogrammetry combined with close-range photogrammetry, fine 3D scene model construction and human-computer interactive for constructing high definition forest road map. And this method can provide a low-cost and high-efficiency way for constructing high definition forest roads map, and also can better provide basic map data for forest management activities. Show more

Keywords: High definition map, forest road, cartography, Menggongshan Forest Farm, forest

DOI: 10.3233/JCM-226621

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 573-587, 2023

Authors: Xiao, Huijun | Jiang, Ensong | Xi, Guangliang

Article Type: Research Article

Abstract: The feature extraction of Gaofen-2 Remote Sensing Image (RSI) has problems such as poor extraction accuracy and large noise reduction error. Therefore, this paper designs an RSI feature extraction method based on high score 2 wavelet transform (WT). The RSI is collected with the help of Gaofen-2 satellite and high-resolution remote sensing technology, the key points of the image are determined through the Gaussian difference scale space, and the key points of the edge are judged by the peak curvature value of the difference function at the edge junction, so as to complete the RSI acquisition. Specific filtering and spatial …domain transformations are used to remove image noise and improve the quality of RSI. The mean shift (MS) algorithm is used to iteratively find the area with the most dense sample points in the RSI space, complete the image analysis, and realize the preprocessing of the high score 2 RSI. The linear features of the RSI are determined by the WT algorithm, and the image threshold is set for feature extraction of the high score 2 RSI. The experimental results show that in the RSI noise reduction error analysis of different methods, the noise reduction error curve of the sample RSI of the method proposed in this paper has the lowest trend, which is always lower than 2%. Compared with the two methods proposed before, the error is higher. At the same time, in the accuracy analysis of key point feature extraction, the proposed scheme has better accuracy. Therefore, it can be seen that this method has better comprehensive performance, and the proposed method can effectively improve the feature extraction accuracy of RSI and reduce the noise in RSI. Show more

Keywords: WT, high score 2 RSI, feature extraction, peak value of difference function, mass spectrometry algorithm

DOI: 10.3233/JCM-226604

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 589-603, 2023

Authors: Zhao, Wei | Zhang, Shuai | Li, Xin

Article Type: Research Article

Abstract: The widespread development of big data and artificial intelligence technology has brought a new development path to digital media technology at this stage. By applying virtual reality technology to multiple areas of digital media, digital media technology has fully demonstrated the actual ability of the scene structure of virtual reality technology in film and television production, game scene settings, urban planning, construction tourism and other industries. The development of digital media technology has brought new development space. The application of virtual reality technology can further shorten the distance between customers and information providers, bring the development of digital media technology …into a new fast lane, and further increase the efficiency of digital media information dissemination. This article uses data analysis methods to build an evaluation model, study virtual reality technology in terms of technological coverage, and further proves by data theory that virtual reality technology brings a new direction and role in the development of digital media technology. Show more

Keywords: Big data, artificial intelligence, virtual reality, digital media, impact research

DOI: 10.3233/JCM-226611

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 605-615, 2023

Authors: Yue, Junping

Article Type: Research Article

Abstract: With the development and progress of various sensors, the Internet of Things technology has continued to penetrate into people’s lives. Successful application cases of the Internet of Things technology have been seen in various industries. Some scholars have begun to try to apply the Internet of Things technology to the management of various industries. Deep learning technology belongs to the category of artificial intelligence technology. Its main goal is to combine a large number of training samples to train the trained object into an object that can learn sample patterns independently. At present, deep learning has a large number of …applications in various intelligent operations and key intelligent recognition fields. Due to the characteristics of its learnable training set, deep learning techniques are often used in the direction of decision analysis. The research adopts a combination of questionnaire survey and modeling analysis to explore the construction of in-depth learning methods for enterprise management intelligent decision-making in the context of the Internet of Things. The research was conducted by telephone interview and online questionnaire, and was supported by nearly 100 technical backbone personnel from 25 large enterprises. The research finds that applying the Internet of Things and deep learning technology to enterprise intelligent management decisions can improve the decision-making accuracy of enterprises, and also provide enterprises with more significant decision-making analysis advantages in the industry competition. This paper first describes the concepts of the Internet of Things, deep learning and intelligent decision-making of enterprise management. Then, in order to sort out the problems existing in the current intelligent decision-making of enterprise management, the author conducted interviews and questionnaires. Through the analysis of the questionnaire data, he found the problems existing in the current intelligent decision-making of enterprise management. Finally, he designed a new strategy of intelligent decision-making of enterprise management based on the Internet of Things and deep learning technology, through the simulation and subsequent investigation and analysis of the newly designed strategy. It is found that the enterprise management intelligent decision-making method designed by combining the Internet of Things and deep learning technology is superior to the traditional enterprise decision-making method in all aspects. The design of the system has been reformed mainly from the aspects of human resource management, digital file management and real-time monitoring of production and operation, so that the popularity of the enterprise’s comprehensive information management has reached 84.2%, the efficiency of intelligent decision-making increased by 28.7% on average. The achievements of the research not only prove the role of IoT technology in promoting enterprises’ in-depth learning, but also put forward new ideas for enterprises’ scientific decision-making. Show more

Keywords: Internet of Things, deep learning, enterprise management, intelligent decision-making

DOI: 10.3233/JCM-226613

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 617-627, 2023

Authors: Sui, Lijuan | Zhang, Zhe | Zhang, Xuzhi

Article Type: Research Article

Abstract: With the gradual urbanization of the countryside, people’s lifestyles have also undergone tremendous changes. Most people tend to live in the countryside, and people also choose tourist attractions with a rural flavor when traveling. This social background continues to promote the development of rural eco-tourism. develop. While the development of rural eco-tourism is driven by the dividends of the times, it may also be affected by various factors and lead to operational difficulties. In order to keep rural eco-tourism scenic spots in a profitable state, a comprehensive evaluation of rural eco-tourism has become the focus. The method of comprehensive evaluation …of rural ecotourism is mainly completed by combining AI algorithms, big data and other auxiliary tools. However, due to the variety of evaluation-related factors involved in the comprehensive evaluation of rural ecotourism, the above evaluation methods cannot fully take into account the rural areas. All aspects of the comprehensive evaluation of ecotourism, so it is necessary to use a method that can complete an effective comprehensive evaluation with less evaluation-related factors to conduct a real evaluation of rural ecotourism. The grey clustering evaluation model is an evaluation method evolved on the basis of the research of Chinese scholars. It can classify and predict the categories according to some characteristics of the clustered objects, which effectively solves the inaccuracy and considerations existing in various current evaluation methods. Incomplete situation. This paper firstly sorts out the grey clustering method and related concepts and theories of rural ecotourism data. After a detailed analysis, and then combined with the gray clustering model to improve the algorithm, an evaluation method with better performance than the traditional gray clustering method was designed. It is found that the improved grey clustering method has more advantages than the method of AI algorithm, big data algorithm and other auxiliary tools for comprehensive evaluation of rural ecotourism. Show more

Keywords: Grey clustering, rural ecotourism, comprehensive evaluation

DOI: 10.3233/JCM-226617

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 629-638, 2023

Authors: Xiang, Shiqian

Article Type: Research Article

Abstract: The visual communication design and application under Big data and Artificial intelligence technology have developed widely, and the demand for comprehensive talents is getting higher and higher. This study conducted a wide range of investigations through the actual situation of visual design applications under Artificial intelligence and Big data technology, and conducted in-depth analysis of the status and existing problems in the entire visual communication design, comprehensively using data analysis methods, and designing the design process. Among them, the effect of technical coverage is in-depth evaluation, and an effective analysis of Artificial intelligence technology has promoted the role of visual …communication design. In the entire design process, the deficiencies and shortcomings of existence have been adopted to laid a more solid foundation for the extensive development of the design. The research combines data analysis and modeling calculation. Through the comparison of several data in the field of visual communication in the era of Artificial intelligence in recent years, it summarizes the internal laws of its development, and then assigns values to various influencing factors through modeling. So as to explore a more optimized development direction and strategy. Show more

Keywords: Big data, Artificial intelligence, visual communication design, application research

DOI: 10.3233/JCM-226627

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 639-649, 2023

Authors: Lv, Hua

Article Type: Research Article

Abstract: In the background of the widespread development of big data technology, the actual behavior of e-commerce consumers is affected by different consumer environment and consumer demand. This article conducts in-depth inquiry and analysis of the behavior of different e-commerce users, and more accurately conducts a comprehensive analysis and effective assessment of various factors that affect consumer behavior. The factors and measures of consumer behavior are comprehensively judged to get the evaluation model closer to consumer behavior. By conducting a comprehensive full-process research on different e-commerce platforms, consumer behavior, consumption habits, and consumption processes, a comprehensive full-process research, more effective channel …methods and dependence on consumers’ purchase of goods, conduct a comprehensive research other factors of behavior, such as transportation logistics, environmental conditions, advertising, and other factors, conduct comprehensive judgment and analysis, and provide important theoretical basis and certain research in order to promote and improve the orderly development of consumer behavior and e-commerce environment. The research adopts modeling and analysis methods, through the evaluation of the research model, it can be seen that under the background of big data, e-commerce consumer behavior presents the trend of data, diversification and complexity. Factors affecting consumer behavior are more diverse and complex. It effectively expands the research field of e-commerce consumer behavior analysis, and provides scientific reference for the development of e-commerce. Show more

Keywords: Big data technology, e-commerce platform, consumer, consumer behavior, analysis and research, online shopping platform, e-commerce users, behavior, data mining

DOI: 10.3233/JCM-226628

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 651-661, 2023

Authors: Wang, Yongke

Article Type: Research Article

Abstract: The engineering project warehouse can combine various sensor devices and smart devices under the Internet of Things technology to realize the convenient management of the warehouse. The Internet of Things technology combined with the machine learning model can make various industries transform to intelligence. The use of IoT technology and machine learning models for warehouse management can achieve an unattended warehouse effect. The Internet of Things has gradually developed into the intelligent technology that attracts the most attention in various industries with the advancement of electronic components required by various sensors. Combining various sensor devices and smart devices under the …Internet of Things technology to achieve convenient management of warehouses, its intelligent management of warehouse security, environment, fire protection, energy consumption, etc. can save a lot of manpower and material resources, and improve the project warehouse, Utilization of supplies. Machine learning technology is a new type of computer self-learning technology produced along with artificial intelligence technology, which can combine the corresponding algorithm and the definition of the developer to realize the learning of the defined transaction. Because the way of this operation is similar to the human learning ability, machine learning Warehouse management for engineering projects will maximize the unattended effect of the warehouse. The research adopts a combination of questionnaire survey and modeling analysis. At first, analyzes the current demand points of engineering project warehouse management in various industries through a questionnaire survey, and designs the Internet of Things auxiliary scheme for engineering project warehouse management according to the demand points. The IoT-assisted machine learning model compares the IoT engineering project warehouse management solution without machine learning model with the IoT engineering project warehouse management solution with machine learning. It is found that the solution with machine learning model can effectively improve the engineering project warehouse management. abilities in all aspects including the effective utilization rate of necessities, manpower saving and safety accident control, which proves that the research has high use value. Show more

Keywords: Engineering project, warehouse management, Internet of Things, machine learning

DOI: 10.3233/JCM-226630

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 663-673, 2023

Authors: Wang, Yungang

Article Type: Research Article

Abstract: In daily life, English is increasingly used in various scenarios, and the technology of translation using machines and others is gradually maturing, but there are still cases of inaccurate translation. To enhance translation’s accuracy, this study optimizes the method of fuzzy semantic selection, and then optimizes the method of domain analysis combined with neural networks to improve the accuracy of machine translation in different domains. The accuracy of the optimized neural network tends to be stable when the number of iterations is 15, the accuracy is 0.96, the accuracy of the traditional neural network is 0.91, and RNN is 0.82. …Compared with the benchmark system, the bilingual mapping model has increased by 0.67% in the news field and 0.56% in the education field. The precision, recall and F value of machine translation are 93%, 86% and 0.8 respectively. The comprehensive experimental results show that the selection method based on fuzzy semantics, combined with the domain analysis method of network neural, can remarkably enhance the accuracy. Show more

Keywords: Machine translation, fuzzy semantics, neural network, multisemantics, domain analysis, bilingual mapping

DOI: 10.3233/JCM-226635

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 675-687, 2023