Journal of Computational Methods in Sciences and Engineering - Volume 24, issue 1

Authors: Wang, Songcen | Chen, Hongyin | Li, Dezhi | Li, Jianfeng | Liu, Kaicheng | Zhong, Ming | Jia, Xiaoqiang | Jin, Lu

Article Type: Research Article

Abstract: With the development of the economy, people’s demand for green energy has increased significantly. However, the traditional single fossil energy supply system cannot meet the needs of low-carbon. Therefore, this study employs energy hub to establish a multi-energy flow network that enables the integration of carbon flow within the network. Additionally, by utilizing the multi-energy flow trend, a carbon flow tracking method is adopted to achieve real-time carbon flow calculation. Results show that this network calculates the electricity cost of 20043 yuan, gas cost of 67253 yuan, and carbon emission cost of 3152 yuan. Compared with the traditional energy flow …system, gas cost is reduced by 4.3% and 1.7%, electricity cost by 21.3% and 15.0%, and carbon emission cost by 8.7% and 6.6%. The two-way sharing carbon flow calculation model calculates that the user side and power supply side of the node each bear half of the network loss, proving two-way sharing effectiveness. Test results on IEEE5 machine 14-node system show that the calculation method can accurately find high-emission and low-emission areas, making the carbon emission allocation between power generation and user more fair and reasonable. This research can effectively reduce emissions cost, accurately calculate emissions flow in real time, and facilitate reasonable emission reduction planning. Show more

Keywords: Energy supply, energy hub, carbon flow, tidal current, green and environmentally friendly energy, multi energy flow power flow network

DOI: 10.3233/JCM-247175

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 3-18, 2024

Authors: Li, Lixin | Lv, Yan | Sun, Bo | Wang, Miao | Chen, Bin | Li, Zeke | Fan, Haiwei

Article Type: Research Article

Abstract: Against the backdrop of global attention to climate change and environmental sustainability, the development timing and comprehensive cost of regional renewable energy power generation projects have become a focus of attention. By constructing effective models to evaluate them, it can help promote the healthy development of renewable energy projects. The research aims to quantitatively evaluate the development status of local renewable energy projects by constructing a comprehensive evaluation model, minimize information loss, and improve the accuracy of evaluation results. This study adopted a comprehensive evaluation model that combines Analytic Hierarchy Process (AHP) based on accelerated genetic algorithm, entropy weight method, …and ideal point method. Firstly, the subjective weights of the development evaluation indicators for regional renewable energy power generation projects are calculated. Secondly, the entropy weight method is used to analyze the trend of each indicator and obtain objective weights. Finally, combined with the objective weights and the evaluation results calculated using the TOPSIS method, a comprehensive evaluation of renewable energy power generation projects in various regions is conducted. Through analysis, the core indicators of the development level of renewable energy power generation projects in various regions show specific performance, such as Hebei’s evaluation value of 0.4945 in the proportion of comprehensive energy development, and Inner Mongolia’s evaluation value of 0.4045 in the proportion of comprehensive energy installed capacity. Meanwhile, genetic optimization methods exhibit significant advantages in the calculation of optimization schemes compared to dynamic programming methods, possessing strong global search capabilities and high-precision solutions. This study provides a new research method and approach for the evaluation of regional renewable energy power generation projects, demonstrating the practical value and certain advantages of the research method. Show more

Keywords: Integrated evaluation model, timing optimization, energy system, renewable energy, power generation projects, sustainable, AGA-AHP

DOI: 10.3233/JCM-247173

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 19-36, 2024

Authors: Meng, Junxia | Deng, Hanjun | Yu, Minqi | Yang, Shuai | Tan, Huang | Chen, Hongyin

Article Type: Research Article

Abstract: Day-ahead scheduling strategy is an effective way to improve the renewable energy accommodation. To increase the renewable energy accommodation in the regional power grids, reduce the total costs of the power system, and improve the supply reliability of the power system, this research suggests a multi-time-scale “source-storage-load” coordinated dispatching strategy that considers the distribution and characteristics of pumped energy storage and loss of the network. Taking the wind curtailment penalty costs, the system operating costs, and the load loss penalty costs as the objective functions, a day-ahead coordinated scheduling strategy for source storage and load considering demand response and lines …loss is established. Finally, the commercial software package CPLEX is called through the MATLAB platform to complete the optimization of mixed integer programming. Simulation results shows that the proposed scheduling strategy could build the power generation plant, effectively adjust the output power of pumped storage, and regulate the assumption of translationable load and transferable load. Show more

Keywords: Day-ahead coordinated scheduling strategy, line loss, source-storage-load, CPLEX, renewable energy

DOI: 10.3233/JCM-247171

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 37-49, 2024

Authors: Gong, Taorong | Chen, Songsong | Shi, Kun | Chai, Zhichao | Wang, Yu

Article Type: Research Article

Abstract: With the rapid development of renewable energy and the urgent need for global carbon emission reduction, virtual power plants have become a high-profile energy management model that can integrate multiple energy resources. How to effectively integrate renewable energy to reduce carbon emissions, how to optimize the use of different energy resources, and how to fairly distribute economic benefits within virtual power plant clusters while encouraging the reduction of carbon emissions are issues that need to be addressed in research. The study first established a virtual power plant model and conducted in-depth optimization for its economic and environmental indicators. Subsequently, the …study constructed a game model within the virtual power plant cluster, aiming to solve the problem of income distribution in this diversified energy system. The research results found that commercial users have the highest carbon emissions, followed by industrial users, while residential users have the lowest carbon emissions. In terms of optimized user electricity consumption behavior, the peak-to-valley difference rate of industrial users has been reduced by 17%, and the daily load rate has increased by 6%; the peak-to-valley difference rate of commercial users has been reduced by 12%, and the daily load rate has increased by 6%; The peak-to-trough difference rate for residential users decreased by 8%, and the daily load rate increased by 4%. In addition, the research also proposes a method of internal revenue distribution of virtual power plant clusters based on a carbon reward and punishment mechanism, which provides a new way for the synergy effects and economic benefit distribution of virtual power plants. Research is of positive significance in solving pressing issues in the field of energy management and provides strong support for the development of future sustainable energy systems. Show more

Keywords: Virtual power plant, carbon reward and punishment mechanism, internal revenue sharing, shapley value model, IBDR

DOI: 10.3233/JCM-247169

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 51-68, 2024

Authors: Wang, Yu | Tang, Bihong

Article Type: Research Article

Abstract: As the goal of “double carbon”, integrated energy systems aiming at the development of low-carbon economy are developing rapidly, and carbon capture and other emission reduction technologies are gradually gaining more extensive development space. For controlling carbon emissions and enhance the consumption of renewable energy. This work proposes to introduce carbon capture technology in the framework of integrated energy system and optimize the energy dispatching of integrated energy system in multiple time scales, and design a multi-time scale optimization model of integrated energy system with carbon capture. Based on the basic architecture of a low-carbon integrated energy system, this study …analyzes the power characteristics of each unit of the integrated energy system, which consists of thermal power units, gas turbines, electric boilers, batteries, gas storage, heat storage, etc. By studying the energy conversion and storage processes of each unit, a power model of each unit of the integrated energy system is established. On this basis, the relationship between carbon emissions and unit output of thermal power units and gas turbines was studied, and a carbon emission model for the energy supply unit in the comprehensive energy system was established. At the same time, in order to solve the problem of carbon emission reduction under the day ahead scheduling plan of the integrated energy system, considering the emission reduction goals and system operation security factors, the study analyzed the economic model and carbon emission model of the integrated energy system, established the day ahead low-carbon scheduling model of the integrated energy system, and reasonably planned the output of each unit that can achieve the carbon emission reduction goals on the premise of meeting the balance of supply and demand. The innovation of the research method of this paper is that this paper establishes a multi time scale rolling optimization model under the emission reduction goal of the integrated energy system. Based on the day ahead scheduling scheme obtained in the day ahead low-carbon scheduling phase, the day ahead plan is first revised through 4 h rolling scheduling in the day; Then, with the goal of minimizing the adjustment amount, fine tune the unit output within 15 minutes to provide a daily output plan for subsequent low-carbon emission reduction targets. The outcomes indicate that in the practical application, the carbon emission of the optimized model in the peak hour 11:00 to 12:00 phase is 118 tons, which is 7 tons less than the 125 tons of the traditional model. In summary, it demonstrates that the studied multi-timescale optimization model of integrated energy system with carbon capture has good application. We have studied and analyzed the low-carbon implementation mechanism of coordinated cooperation in multiple time scales, and constructed a multi time scale rolling optimization model, laying a theoretical foundation for subsequent low-carbon scheduling research. This enables the system to formulate more accurate and reasonable scheduling plans, while improving the low-carbon performance and economic benefits of the system, providing reference for the low-carbon development of the power system. Show more

Keywords: Carbon capture, multiple time scales, integrated energy systems, optimal dispatch, low carbon economy, energy conversion

DOI: 10.3233/JCM-247166

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 69-86, 2024

Authors: Zhao, Ying | Liang, Genshun

Article Type: Research Article

Abstract: This paper aims to explore unsupervised cross-lingual word representation learning methods with the specific task of acquiring a bilingual translation lexicon on a monolingual corpus. Specifically, an unsupervised cross-lingual word representation co-training scheme based on different word embedding models is first designed and outperforms the baseline model. In this paper, we adeptly tackles the obstacles encountered in higher education foreign language teaching and underscores the necessity for inventive teaching methods, and design and implement a linear self-encoder-based principal component acquisition scheme for the interpoint mutual information matrix obtained from a monolingual corpus. And on top of this, a collaborative training …scheme based on linear self-encoder for cross-language word representation is designed to improve the learning effect of cross-language word embedding. The results of the study show that the most obvious rise in the pre and post tests of the experimental class in the practical application of the foreign language teaching model based on the method of this paper is the word sense guessing, which rose by 23.12%. Sentence meaning comprehension increased by 23.39%, main idea by 16.61%, factual details by 15.47%, and inferential judgment by 10.28%. Thus, the feasibility of the unsupervised cross-linguistic word representation learning collaborative training method is further verified. Show more

Keywords: Collaborative training, unsupervised learning, monolingual corpus, cross-lingual word representation, foreign language teaching

DOI: 10.3233/JCM-237113

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 87-103, 2024

Authors: Jiang, Jiaying | Wang, Zhixiu | Tao, Sha | Tan, Xinyi | He, Ying | Pan, Wenchao

Article Type: Research Article

Abstract: The new crown pneumonia epidemic is raging, in the context of global integration, the scope of the impact of this sudden event spread around the world, the stock market has not been spared, the financial risk has increased dramatically compared with the past, the emergence of the epidemic has led to the spread of investor panic, March 2020, the U.S. S&P 500 index appeared in the four plunge, and led to the market trading meltdown, the world’s financial markets have had an extremely serious impact. The study of the impact of Xin Guan Pneumonia on the company’s stock returns is …not only conducive to enriching the theoretical study of public health emergencies, but also conducive to improving the coping strategy, stabilizing the general economic market, and enhancing the public’s awareness of risk response. This paper compares the effect of the four intelligent algorithms of chaotic particle swarm algorithm, chaotic bee colony algorithm, chaotic fruit fly algorithm and chaotic ant colony algorithm combined with neural network on the prediction of the stock price trend of Yunnan national culture, and the study shows that the speed of convergence of the chaotic particle swarm optimization neural network and the speed of descent is better than that of the two models of chaotic fruit fly and chaotic bee colony, and the coefficients of decision of the chaotic particle swarm optimization neural network are higher than that of the other three models, and the errors are lower than the other three models. Indexes are lower than the other three models and have high accuracy in stock prediction of Yunnan ethnic culture, this finding emphasizes the potential of PSO-BP model to provide robust stock market prediction, which is important for both investors and policy makers in dealing with volatile market conditions. Show more

Keywords: Chaotic particle swarm optimization algorithm, BP neural network, ethnic culture of yunnan, stock prediction

DOI: 10.3233/JCM-237119

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 105-120, 2024

Authors: Zhou, Fangjian | Guo, Hua | Lei, Yinchun | Tang, Chengling | Mo, Xiaoyin

Article Type: Research Article

Abstract: In order to scientifically evaluate the emergency management capabilities of major cities in China, this article conducts a comprehensive study on the input and output indicators of emergency response in each city. A two-stage network DEA model was used to construct an evaluation model that reflects the emergency management capacity of cities. A dataset containing emergency management data from 36 well-known cities in China was selected to effectively evaluate its performance, and the city that demonstrated the most effective input-output ratio in the field of emergency management was ultimately determined. The research results show that using a two-stage network DEA …model as the foundation to construct an evaluation model that reflects urban emergency management capabilities can promote a wise combination of subjective and objective evaluations, and achieve scientific investment in urban emergency assets. Show more

Keywords: Emergency management, novel network DEA, data envelopment analysis, radial distance

DOI: 10.3233/JCM-237115

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 121-133, 2024

Authors: Wu, Qianqian

Article Type: Research Article

Abstract: Teaching evaluation is a key initiative to improve the quality of education and teaching. The research significance of this study is rooted in addressing the limitations of the traditional evaluation of teaching quality (ETQ) model, which often relies on a single evaluation index, exhibits a one-sided perspective, and suffers from pronounced subjectivity. In this context, this paper delves into the application of the backpropagation neural network (BPNN) to enhance and refine the ETQ model. The intelligent ETQ model was constructed and utilized in network English teaching to enhance the effect and quality of network English teaching. By analyzing the characteristics …and needs of network English teaching, the advantages of BPNN in the ETQ were explored. The intelligent evaluation model was constructed, and its application effect in network English teaching was studied and evaluated. The total number of students satisfied with the BPNN based network English ETQ model was 151, with a total satisfaction rate of 75.5%. The ETQ model on the basis of BPNN was applied to network English teaching, which helped the average final score of Class 2 improve by 5.44 points compared to the division exam. The ETQ model based on BPNN was applied to network English teaching, which can improve the rationality of teaching evaluation and help improve students’ school English proficiency. Show more

Keywords: Network english teaching, evaluation of teaching quality, back propagation neural network, evaluating indicator, analytic hierarchy process, radial basis function

DOI: 10.3233/JCM-237117

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 135-151, 2024

Authors: He, Yongting | Liu, Jiandong

Article Type: Research Article

Abstract: The EI is an important pillar of modern economic development and a key factor in ensuring national strategic energy security. The upgrading of China’s Energy Industry (EI) faces a series of problems and challenges, such as excessive energy production, difficulty in energy technology innovation, and low energy efficiency. The significance of this study lies in its endeavor to tackle these challenges by focusing on several facets, including the promotion of innovation in energy technology and the enhancement of energy management. Utilizing the Kuznets Curve (KC) theory and considering energy export restrictions (ER) as a constraint, the study analyzed the impact …of China’s EI upgrading. It analyzed the relationship between changes in indicators such as EI resource utilization rate, degree of ERs, export proportion, and resource allocation proportion of energy enterprises and the impact of China’s EI upgrading. According to the experimental results, it can be concluded that when the resource utilization rate was between 30% and 60%, the energy export volume showed a significant growth trend. As it gradually approached saturation, the contribution of energy production growth began to weaken and showed an inverted U-shape. Examining how the expansion of Economic Relations (ERs) affects the enhancement of China’s Economic Infrastructure (EI) within the framework of the Knowledge Capital (KC) can provide valuable insights. It offers guidance on striking a balance between exports and domestic demand in China’s economic development, facilitating the formulation of export policies, supporting structural adjustments and advancements in China’s EI, and contributing to the promotion of sustainable development (SD). Additionally, this analysis aids in preventing potential issues and safeguarding both the ecological environment and the interests of citizens. Show more

Keywords: Upgrading the energy industry, Kuznets curve, export restrictions, resource utilization rate, inverted u-shape

DOI: 10.3233/JCM-237121

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 153-164, 2024

Authors: Yang, Wenqian | Li, Cheng

Article Type: Research Article

Abstract: This study aims to evaluate the quality of physical education in colleges and universities by using the evaluation method based on fuzzy logic. First, summarize the basic concept of fuzzy logic and its application in the evaluation process. Then, a physical education quality evaluation index system covering teaching quality and students’ physical quality, teachers’ team construction, sports facilities and management is constructed. Then, the evaluation object and evaluation level are determined, and the specific evaluation results and ranking are calculated by fuzzy comprehensive evaluation model. In the empirical analysis, use the simulation data for model application and result analysis, and …further find the problems existing in college physical education. Finally, in view of these problems, a series of improvement and optimization suggestions are put forward. This study shows that the evaluation method of physical education quality based on fuzzy logic can effectively reflect the diversity and complexity of education quality, and provide a practical evaluation tool for colleges and universities. At the same time, this study also provides a reference for other universities to help them better understand their own problems, so that they can take effective measures to improve. In addition, this method can be applied to other fields of education quality evaluation in the future, so as to provide more useful information for education reform and development. Show more

Keywords: Physical education in colleges and universities, quality evaluation, fuzzy logic, index system, comprehensive evaluation model

DOI: 10.3233/JCM-237029

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 165-181, 2024

Authors: Liu, Mengran

Article Type: Research Article

Abstract: The rise of social networking in today’s society has brought convenience to people’s lives, but at the same time people are also suffering from cyberbullying. How to check these bullying languages has become a popular problem. As text is an important vehicle for online social networking, the natural language learning, representation, and training becomes a necessary work for cyberbullying detection. In this paper, we summarize and analyze the existing work by studying it, and then finally propose new ideas and experiments. The specific method is based on the LSTM model, in which the parameters and dimensions are adjusted to demonstrate …the best results of the model. And a user rating system is used to detect bullying more effectively. Show more

Keywords: Cyberbullying, LSTM, natural language, cyberbullying detection, machine learning

DOI: 10.3233/JCM-237088

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 183-192, 2024

Authors: Shao, Mingzhen | Yuan, Pei | Zhao, Rui | Gu, Yanyan

Article Type: Research Article

Abstract: Based on panel data of 31 provinces in China from 2000 to 2019, this study explores the complex dynamic interaction between scientific and technological innovation, industrial structure transformation and economic development by building PVAR model. After GMM estimation, impulse response function analysis and variance decomposition analysis, the following conclusions are drawn: Technological innovation has a significant promoting effect on economic development, and economic development can also promote technological innovation; Technological innovation has a positive impact on industrial structure transformation, while industrial structure transformation has a slight negative impact on technological innovation; Economic development can lead to industrial structure transformation, but …the impact of industrial structure transformation on economic development is not significant. Show more

Keywords: Sci-tech innovation, industrial structure transformation, economic development, PVAR model

DOI: 10.3233/JCM-237056

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 193-200, 2024

Authors: Tang, Huihua

Article Type: Research Article

Abstract: With the rapid development of vocational undergraduate education, the construction of teachers is very important to improve the quality of education and train outstanding talents. This study takes deep learning as the theoretical basis to explore the construction of vocational undergraduate education teacher team based on deep learning. Through comprehensive literature review, quantitative research methods and questionnaire design, the current situation of vocational undergraduate education teachers is deeply analyzed, and the application potential of deep learning in teacher training is discussed. The research results show that deep learning can provide new teaching tools and techniques to promote the professional development …of teachers and improve teaching effectiveness. However, there are also some problems and challenges in practical application, such as teachers’ cognition and application level of deep learning need to be improved. Therefore, this study puts forward some strategies to solve these problems, and looks forward to the future development of vocational undergraduate education teacher team construction. Show more

Keywords: Deep learning, vocational undergraduate education, construction of teachers, quantitative research, questionnaire

DOI: 10.3233/JCM-237041

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 201-216, 2024

Authors: Chen, Yafang

Article Type: Research Article

Abstract: This study aims to explore the application of deep learning technology in the translation of children’s picture books. By analyzing the existing translation of children’s picture books, we extract the key factors to be considered in the translation process, and design a deep learning model to deal with these factors to achieve high-quality translation. At the same time, a picture book image recognition system is also implemented, which can understand the image content in the picture book and integrate these contents into the translation. Through continuous training and optimization of the model, an efficient picture book translation tool is obtained. …In addition, the performance of the model in practical applications was evaluated, and the practical impact and value of deep learning in children’s picture book translation was explored through user feedback and surveys. Show more

Keywords: Deep learning, children’s picture books, machine translation, image recognition, model optimization

DOI: 10.3233/JCM-237052

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 217-233, 2024

Authors: Yan, Jing | Chen, Aiping | Wang, Haihua

Article Type: Research Article

Abstract: This study explores the application of big data in the field of English learning, focusing on its influence on the analysis of English learning behavior and the effect of teaching intervention. Through experimental design and data analysis, the research results show that big data analysis can reveal the learning behavior pattern of learners, and provide personalized teaching intervention according to individual characteristics, so as to improve the learning effect. The study also found that the experimental group received personalized teaching intervention, English learners’ academic performance and learning motivation significantly improved. However, this study faces the limitations of sample representativeness and …consistency of teaching interventions. Future studies can further expand the sample size and strengthen teacher training to improve the generalization and reliability of research results. Show more

Keywords: Big data analysis, english learning, learning behavior, individualized teaching intervention, learning effect

DOI: 10.3233/JCM-237016

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 235-251, 2024

Authors: Lai, Qingying | Guo, Shudong | Zhao, Chen | Ding, Chuanchen | Huang, Wenzheng

Article Type: Research Article

Abstract: As the commercialization of maglev trains continues to accelerate, effective improvement of maglev train operation has become a topic for researchers. The train headway of the maglev is the preparation basis for the train timetable and is also an essential factor affecting the line capacity utilization. This paper proposed an approach to estimate the train headway by considering the characteristics of partitioned control of maglev operations. First, we build the tracking model for maglev with the theory of blocking time, in which the train speed profile is the key input source. Then, a customized method is proposed to estimate the …minimum headway of maglev trains. According to the experiment, we can effectively obtain the minimum train headway by the approach, and the result of improving the maglev line capacity utilization is verified. Show more

Keywords: Maglev, headway, blocking time, train speed profile

DOI: 10.3233/JCM-237058

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 253-262, 2024

Authors: Wang, Yong

Article Type: Research Article

Abstract: With the rapid development of information technology, electronic signature plays an increasingly important role in people’s production practice. However, there are a large number of hackers maliciously stealing information in the network. In order to avoid this phenomenon, we urgently need to strengthen the research on online electronic signature recognition technology. Based on the sparse classification technology of neural model, this paper constructs an online electronic signature recognition model by using convolutional neural network and sparse classification technology. We first extract the local features of online electronic signatures, construct feature vectors and perform sparse representation. Sub-model we construct a scheme …for online electronic signature recognition based on neural models and sparse classification techniques using a combination of algorithms. We first extract the local features of online electronic signatures, construct feature vectors and perform sparse representation. At the same time, the features in the training image set are extracted, local feature sets are constructed, feature dictionaries are created, and the vectors in the feature dictionaries are matched with the global sparse vectors constructed by the electronic signatures to be detected, and the matching results are finally obtained. At the same time, the features in the training image set are extracted, the local feature set is constructed, the feature dictionary is created, and the vector in the feature dictionary is matched with the global sparse vector constructed by the electronic signature to be detected, and finally the matching result is obtained. In order to verify the accuracy of the model, we first extracted 1000 respondents for online e-signature recognition experimental results show that the recognition accuracy of online e-signature has been significantly improved. Finally, in order to determine the optimal number of training sets for the model constructed in this experiment, we analyzed the correlation between training and sample size and recognition accuracy. Finally, it was concluded that the recognition accuracy increased with the increase of the number of training samples. Electronic signatures can quickly examine the signature results, and electronic signature recognition can be used to fix and tamper-proof evidence to enhance the security and trustworthiness of signatures, and it is imperative to improve the security of electronic signatures. In this paper, we study online electronic signature recognition technology, using neural model and sparse classification to construct an efficient and accurate recognition model. Experiments show that the model is effective and the number of training samples affects the recognition accuracy. This paper provides a new approach for the development of this technique. When the training samples are greater than 1300, the recognition accuracy is stable at 95%. This research has certain theoretical and practical significance, and promotes the rapid development of online electronic signature recognition. Show more

Keywords: Neural model, sparse classification, online electronic signature

DOI: 10.3233/JCM-237025

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 263-275, 2024

Authors: Wang, Qian | Tian, Limei | Yan, Hua | Zhang, Guodong | Yin, Huanhuan

Article Type: Research Article

Abstract: Since current real-name management for construction workers is unreasonable, this study has divided the management levels of construction companies into five categories, based on their IT applications. Apart from adopting literature induction approach and the project management maturity model (PMMM), the study also considers the six modules of human resource management. It has solicited expert opinions and evaluated them with different indicators and the improved Delphi method. Moreover, analytic hierarchy process (AHP) is employed to determine the algorithm of multiple indicators and the weights. This study has created a system to evaluate the maturity of real-name management of construction workers, …offering reference fo enterprises’ personnel information management. It can also be used for industrial and social supervision to promote real-name management. Show more

Keywords: Real-name system, information management, maturity, evaluation system

DOI: 10.3233/JCM-237034

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 277-287, 2024

Authors: Liu, Hui | Zhong, Xiaohui

Article Type: Research Article

Abstract: With the increasing demand for logistics in modern society, how to achieve low-cost and efficient logistics delivery has become an urgent research topic. A hybrid evolutionary JAYA algorithm (H-JAYA) based on global optimization was designed to address the complex path planning problem of electric vehicles. This algorithm introduces a reverse learning mechanism to calculate the current optimal and worst individuals, while using differential perturbation mechanism and sine cosine operator to update the individual’s position. In addition, the study used the H-JAYA algorithm to construct a corresponding mathematical model for the optimization problem of electric vehicle paths. The results showed that …in the three examples, the H-JAYA algorithm tested the optimal curve convergence speed, and it tended to stabilize after about 30 iterations. Meanwhile, in the RCDP5001 example, the total cost of the H-JAYA algorithm reached the lowest value of 623 yuan. The H-JAYA algorithm has significant advantages in solving the distribution path problem of electric vehicles, and can be well applied to practical logistics distribution, providing effective technical support for modern e-commerce logistics planning. Show more

Keywords: JAYA algorithm, global optimization, logistics and distribution, electric vehicles, e-commerce

DOI: 10.3233/JCM-237047

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 289-301, 2024

Authors: Zhou, Jianhua

Article Type: Research Article

Abstract: In recent years, the continuous growth of global carbon emissions has brought about climate change and global ecological environment problems, as well as severe challenges to the development of human settlements. Based on the concept of low carbon, this paper analyzes and summarizes the current situation of green space in typical residential areas, and quantifies its annual carbon sequestration. Then this paper discusses the design optimization strategy to improve its carbon sink efficiency based on the current situation. Finally, the effectiveness and enforce ability of the optimization strategy are verified by estimating the annual carbon sequestration increase value of the …green space after the optimization strategy is applied to an example. The method has a certain reference value for the design and research of urban ecological human settlements with the concept of green and low carbon. Show more

Keywords: Carbon emissions, sustainable development, living environment, green space

DOI: 10.3233/JCM-237049

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 303-309, 2024

Authors: Liu, Yanming

Article Type: Research Article

Abstract: Motion errors can significantly affect the machining accuracy of MACNC. To reduce the motion errors in the operation of CNC, an error compensation algorithm is proposed in the study. Firstly, the motion error measurement and identification method is proposed, and in this way, the MECA based on the third spline fitting is proposed Finally, the effectiveness is verified by simulation experiments. The proposed error measurement method has high measurement accuracy, and the MECA can effectively reduce the machining error value, and its processing time is only 0.012s. The measurement accuracy of the error measurement method proposed in the study reached …98.95%, which was 4.49% and 4.88% higher than the minimum measurement accuracy based on wavelet denoising and genetic algorithm, respectively. When the number of iterations was 5, all three measurement methods achieved the minimum measurement accuracy, and the minimum measurement accuracy of the proposed measurement method was 91.00%, Compared with the minimum measurement accuracy of 93.65% and 94.26% based on wavelet denoising and genetic algorithm, it has decreased by 2.65% and 3.26%, respectively. When disturbed, the accuracy rate of the error compensation algorithm proposed by the research is 93.9%, which is 2%, 2% and 3.5% higher than the minimum values of 91.9%, 91.9% and 90.4% of the three error compensation algorithms based on BP neural network, Particle swarm optimization algorithm and genetic algorithm, respectively. The above results show that the MECA can effectively achieve the error compensation of MACNC, with a fast processing speed, which can effectively workshop Machining efficiency and quality. Show more

Keywords: Motion error, Multi-axis linkage, CNC, Spline fitting, Error compensation algorithm

DOI: 10.3233/JCM-237027

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 311-325, 2024

Authors: Luo, Shuping | Zhu, Xiaoyun

Article Type: Research Article

Abstract: The high profit of regional investment is often accompanied by high risks, and the prior assessment of investment risks is conducive to avoid investment risks. However, the traditional evaluation methods usually only focus on individual risk factors, and it is difficult to evaluate and manage risks on the whole. Therefore, the study introduces deep learning algorithm, first build regional investment risk evaluation index system, then according to the characteristics of risk evaluation, design based on deep learning regional investment risk evaluation model, the final use parameter based migration learning algorithm and composite correlation coefficient to improve the evaluation model, solve …the problem of insufficient training samples. The test results showed that the randomly selected 50 test samples with two different risk assessment models were 0.80 and 0.86, the deep learning algorithm tested 0.84, and the transfer learning improved model tested was 0.92, with the highest accuracy. This shows that the deep learning regional investment risk evaluation model improved by transfer learning effectively solves the problem of insufficient training data and improves the accuracy of prediction evaluation. In the field of venture capital, the model can help investors to evaluate and predict investment risks more accurately and improve the effect of investment decisions. Show more

Keywords: Risk evaluation, transfer learning, compound correlation coefficient, CNN, regional investment

DOI: 10.3233/JCM-237045

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 327-342, 2024

Authors: Wu, Liu

Article Type: Research Article

Abstract: In order to effectively solve the problem of acquiring knowledge from tactical wargaming data, an overall analysis framework is designed based on the standard process of data mining. The data is analyzed from four aspects: time, space, maneuver path and multi-operator behavior correlation. The behavioral characteristics of single operators at different stages and the spatial distribution of key points such as shooting points, hit points and hidden points, and the association rules of movement, shooting, and occupation between multiple operators are obtained. This will provide commanders with experience and knowledge, help them to quickly accumulate combat experience, and provide behavior …rules and action modes for the development of wargaming AI, effectively improving its intelligent level. Show more

Keywords: Wargaming, time and space distribution, maneuver path, frequent pattern mining

DOI: 10.3233/JCM-237083

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 343-356, 2024

Authors: Liu, Guoqi | Zheng, Qingxi | Niu, Siqi | Ma, Jian

Article Type: Research Article

Abstract: With the rapid development and widespread adoption of wearable technology, a new type of lifelog data is being collected and used in numerous studies. We refer to these data as informative lifelog which usually contain GPS, images, videos, text, etc. GPS trajectory data in lifelogs is typically categorized into continuous and discrete trajectories. Finding a point of interest (POI) from discrete trajectories is a challenging task to do and has caught little attention so far. This paper suggests an LP-DBSCAN model for mining personal trajectories from discrete GPS trajectory data. It makes use of the hierarchical structure information implied in …GPS trajectory data and it is suggested a variable-levels, variable-parameters clustering method (LP-DBSCAN) based on the DBSCAN algorithm to increase the precision of finding POI information. Finally, the Liu lifelog dataset is subjected to a systematic evaluation. In terms of GPS data that are not evenly distributed geographically, the experimental results demonstrated that the proposed algorithm could more accurately identify POI information and address the adverse effects caused by the global parameters of the traditional DBSCAN algorithm. Show more

Keywords: Personal big data, lifelog, points of interest, discrete trajectory, DBSCAN

DOI: 10.3233/JCM-237061

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 357-368, 2024

Authors: Wei, Tingting

Article Type: Research Article

Abstract: English is a common global communication medium for exchanging diverse cultural elements between countries/people. The role of language is significant in developing political and economic aspects between nations. Such developments rely on voluptuous data from the past to the present happenings, reasoning, and conversations. Considering the significance of the English language in international cultural exchange and developments, this article introduces a Harmonious Data Analytical Scheme (DAS)-processed by Deep Learning (DL) paradigm. This scheme analyzes the available and accumulated data for cultural improvements and exchanges between diverse countries. The DL process identifies the matching aspects between the country’s culture and the …accumulated data. Identifying such a point is repeatedly verified for the developments from the beginning to the current level of cultural improvements. The process discards the obsolete cultural data that are less considerable for exchanges and developments in the past. This process refines precise data to be utilized in further cultural exchanges reducing the data handling time and complexity. Finally, the proposed scheme is reliable in identifying the cultural development-based data through the common English language aspects. The DAS-DL method attains Identification rate by 0.98s, refining rate by 0.79% and data accumulation rate by 95.2% compared to existing methods. Show more

Keywords: Big data, cultural exchange, data analytical scheme, deep learning, English language

DOI: 10.3233/JCM-237021

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 369-384, 2024

Authors: Jiang, Dewei | Huang, Xiumei

Article Type: Research Article

Abstract: The measurement process of corporate human capital value ignores the in-depth analysis of the influencing factors of value measurement, which leads to the inaccuracy of the measurement result of corporate human capital value. Therefore, taking an enterprise in Heilongjiang Province as the research object, a measurement model of enterprise human capital value based on binary tree is designed. Establish the corporate human capital value measurement index system, and initially fix the human capital value. Calculate the floating value of human capital under the complete information, and determine the influencing factors of human capital value measurement. The human capital value of …enterprise under incomplete information is calculated to complete the construction of the measurement model of human capital value of enterprise based on binary tree. Taking the actual human resource performance score of an enterprise from 2019 to 2022 as an example, the experiment proved that the design model and the traditional measurement model evaluated the enterprise human resource performance, and proved that the measurement model based on binary tree was more accurate than the traditional model, and the final measurement accuracy of the design model reached 93.5%. Compared with the traditional measurement model ahead of 18.5%–10.3%, compared with the current advanced measurement model ahead of 5.2%–5.7%. The evaluation Angle in the research is slightly lacking of practical significance, and further research can carry out further evaluation on income to maximize the practical significance of the research. However, the model is evaluated from the perspective of pricing, but in real life, the value of enterprise human capital is reflected in income distribution. Therefore, if the measurement of human capital value is combined with income distribution in the next step, the research results will be closer to the actual situation and will have more practical significance. Show more

Keywords: Binary tree, corporate human capital value, options, measurement scale, assessment, human resource development

DOI: 10.3233/JCM-237065

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 385-399, 2024

Authors: Cao, Xianghong | Wu, Yanmin | Wang, Hong | Li, Sen

Article Type: Research Article

Abstract: To meet the needs of professional development promotion through cross-university collaborative construction in the era of Internet+ , a new model of cross-university teaching and research organization is proposed by constructing a regional virtual teaching and research room for remote teaching and research activities among grassroots teaching organizations of different universities, utilizing modern information technology. Led by the national first-class specialty construction site of Building Electrical and Intelligent Specialty at Zhengzhou University of Light Industry, a cross-university regional virtual teaching and research room for this specialty is established in collaboration with other universities offering the same specialty in …Henan province. This paper outlines the efficient and stable operation mechanism for the regional virtual teaching and research room’s multi-university collaborative construction and explores the co-construction path for cross-university regional virtual teaching and research rooms. A high-quality resource sharing platform for multi-university collaborative construction is built within the regional virtual teaching and research room, enabling intercollegiate high-quality resource and outstanding teaching team interconnection, co-construction, and sharing. This approach aims to fully leverage the distinctive features and advantages of the Building Electrical and Intelligent Specialty in each university in the region, promote cooperative development and interdisciplinary integration among partnering universities, and improve the quality of talent cultivation. It may also provide valuable reference and guidance for the collaborative construction of virtual teaching and research rooms across a broader range of universities. Show more

Keywords: Regional, virtual teaching and research room, cross-university teaching and research organization, collaborative construction, building electrical and intelligent specialty

DOI: 10.3233/JCM-237090

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 401-412, 2024

Authors: Zhang, Yiheng | Diao, Weiqing | Nie, Yong | Wang, Qin

Article Type: Research Article

Abstract: In order to improve tourists’ sense of touring experience, this research proposes a signage navigation system for mobile scenic spots. Firstly, the system uses a recurrent neural network algorithm incorporating convolutional neural network for image recognition function to obtain relevant information through image recognition. Then the target localization of the image is performed according to the single-stage target detection algorithm, and the location of the landscape in which the user is located is localized by the recognized image information. The results show that the algorithm can achieve 86.7% recognition accuracy, and it can recognize part of the image samples when …the recognition time reaches the range of 0.8 min–1 min. The single-stage target detection algorithm has a localization accuracy of 97.2% with a minimum loss rate of 1.1%. And the algorithm has high average accuracy and full class average accuracy values. The system has good application value. Show more

Keywords: Vision technology, tourism, signage guidance, cnn-rnn, SSD

DOI: 10.3233/JCM-237032

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 413-426, 2024

Authors: Cui, Shuguang | Wang, Haixia

Article Type: Research Article

Abstract: This paper proposes a sharing algorithm based on blockchain principles to address the issues of data sharing, low efficiency, and performance in traditional systems. The algorithm is integrated with the domain name system to develop a data storage system based on blockchain. The performance of the sharing algorithm is evaluated, and the data storage system is tested. This demonstrates that the sharing algorithm’s average latency is 436 ms and average throughput is 5439 tps. Furthermore, it outperforms the other comparison algorithms. Additionally, the study conducts performance experiments to compare the data storage system. The data storage system proposed in this …study demonstrates a higher average throughput of 6.42*108 tps and a faster data access time of 0.15 s than the other comparison systems. The comprehensive results show that the proposed sharing algorithm and data storage system outperform the comparison algorithm and system in terms of latency, throughput, and data access performance. The constructed model exhibits good centralized and distributed storage crawling performance, which can achieve more secure, efficient, and trustworthy data sharing in distributed network data storage. Show more

Keywords: DNS, blockchain, shared algorithm, distributed network, data storage

DOI: 10.3233/JCM-237038

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 427-444, 2024

Authors: Fan, Yuan | Song, Xiangru | Wang, Rong

Article Type: Research Article

Abstract: The integrated development of culture and tourism public services can better enhance the value of scenic spots, promote the spread of Chinese excellent culture, and drive the development of tourism economy. Big data technology can predict the future development law of transactions based on historical data. It can meet the needs of tourists and tourism enterprises in a targeted manner. This paper aims at the integrated development practice of tea culture and tourism public services in the era of big data, analyzes the influencing factors of the integrated development of tea culture tourism and public services in Tianfu Tea Garden …and the problems existing in the development process of Tianfu Tea Garden, and designs data analysis algorithms through big data technology, and put forward development suggestions combined with big data technology, mainly including improving the industrial chain; improving the overall development scope of the scenic spot; strengthening the quality training of tea garden employees; improving infrastructure; highlighting the connotation of tea culture in scenic spots; developing and researching new tourism products; increase the publicity and construction of scenic spots, so as to provide reference for the development of tea culture and tourism in Tianfu Tea Garden. Show more

Keywords: Big data, integration of culture and tourism, public service development, strategy

DOI: 10.3233/JCM-237036

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 445-462, 2024

Authors: Han, Hongyan | Shi, Ruiying | Zhang, Yaoyao | Li, Na | Fan, Linghe | Zhang, Xing

Article Type: Research Article

Abstract: Feeding on crude oil and activator in porous medium, microbes remain active on the Oil-water interface under simulated reservoir conditions. At the same time, microbes degrade the residual oil and change the wettability of pore wall. Consequently, the displacement exhibits a decrease of 51.86% in membrane residual oil and an increase of 17.44% in recovery compared with water flooding. The Geobacillus stearothermophilus producing bio-emulsifier and its metabolic products can effectively emulsify reservoir crude oil and reduce the oil-water interfacial tension. In the end and the formed emulsion featured high viscosity can improve the oil flow rate and expanded wave volume …of injected fluid. Correspondingly, the cluster-like, columnar residual oil were reduced by 64%, 68% respectively. In the micro porous test cell, the in-situ cultured microbes rely on specific life activities (interfacial tropism and in situ metabolism, etc.) to strip the residual oil off the wall of orifice deep inside the blind-ends, which cannot be achieved by the exogenous injection method. After the in-situ microbial culture process, the residual oil in deep blind-ends was reduced by about 47%, and the recovered oil was increased about 15% compared with exogenous injection method. Show more

Keywords: Geobacillus stearothermophilus, residual oil, in-situ culture, exogenous injection, deep blind-ends residual oil

DOI: 10.3233/JCM-237072

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 463-472, 2024

Authors: Cui, Yongbin

Article Type: Research Article

Abstract: Although picture extraction is challenging, the murals at Dunhuang are historically significant and offer rich content. The work suggests an image segmentation model based on the Mean Shift algorithm and an area salience prioritisation model to extract the cultural aspects in the Dunhuang murals for landscape design. First, an image segmentation model based on the Mean Shift algorithm is established, and then a region salience value calculation method and a region prioritisation method are designed to establish a region salience prioritisation model. The outcomes showed that a segmentation model built using the Mean Shift algorithm in the study processed a …405175 image with a processing time of 3.18 seconds, an edge integrity rate of 88.9%, an accuracy rate of 87.4%, an F-value of 88.7%, and a total of 302 regions. The segmented Dunhuang image featured few noise points and a distinct shape. Salient region transfer path is more regular and more in line with the human visual transfer mechanism thanks to the research design of the region saliency value calculation method, which also improves saliency detection performance. The highest correct rate when dividing the image is 0.97, the highest check rate is 0.8, and the highest F1 value is 1. In conclusion, the study’s methodology has some favourable implications for landscape design and may be effectively used to extract cultural components from photographs. Show more

Keywords: Mean shift algorithm, Image extraction, landscaping, salient region

DOI: 10.3233/JCM-237014

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 473-487, 2024

Authors: Liu, Qifeng | Guo, Lei

Article Type: Research Article

Abstract: Digital publishing is the process of informatizing the content of traditional publishing. It not only involves the processing of information, but also includes the whole process of digital publishing enterprise management and operation. Compared with traditional publishing, digital publishing has a wider distribution channel with the advantages of more diverse forms and marketing aspects, the transition from traditional digital publishing to digital publishing has become an inevitable trend. But there are still many problems in digital publishing in our country. Including the transformation of digital copyright awareness and maintenance of digital copyright, the source and maintenance of digital publishing technology, …and the scarcity of compound talent resources. In order to solve these problems, we must combine the digital publishing industry with modern information technology. This paper builds a digital market preference prediction model based on big data and fuzzy control algorithms. By analyzing and predicting each consumer’s usage information, the digital consumer market preference is obtained. This research uses big data and fuzzy control algorithms to build a consumer market preference estimation model for digital publishing transformation. Through the observation of the consumer market, it can promote digital companies to make effective decisions and conduct reasonable organizational analysis, which can further improve The development process of digital publishing transformation promotes the overall development of the enterprise. Through verification, this model has high accuracy and reliability, can support the operation of actual enterprises, and plays an important role in the development of enterprises. Finally, based on the content of the article research, we put forward the following suggestions for the transformation and development of digital enterprises (1) conduct market analysis through big data and fuzzy control technology, and clarify market positioning (2) promote traditional publishing and digital publishing through big data and fuzzy control technology Integrated Development of Publishing (3) Cultivate Excellent Composite Talents for Digital Publishing Transformation. Show more

Keywords: Big data, fuzzy control, digital publishing marketing, transformation and development

DOI: 10.3233/JCM-237023

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 489-499, 2024

Authors: Li, Yi | Xiong, Yingzhi | Li, Chuzhao | Zhang, Qiang | Gao, Zhenhai | Hu, Hongyu

Article Type: Research Article

Abstract: Instinctive response was produced for protecting drivers from injury when facing incoming collisions. For better understanding it’s influence of lower extremity injury, this study proposed an approach to analyze the collision injury considering the instinctive response posture and musculoskeletal characteristics. 20 male drivers were recruited for an instinctive response test in driving simulator and their lower extremity postures and muscle activation of 8 major ones at the collision moment were collected. The difference between different postures and muscles were analyzed and their influence on injuries were investigated by collision simulation. Results showed that increased possibility for the right leg holding …on the air or even on the accelerator pedal with increased emergency level at the collision moment. Significant difference existed in different muscles between different postures. The introduction of instinctive response changed the driving posture and musculoskeletal characteristics, which further influence the lower extremity injury. This study help understanding the accurate behavioral and injury procedure and providing support for design a better restraint systems. Show more

Keywords: Instinctive response, lower extremity posture, muscle activation, collision injury

DOI: 10.3233/JCM-237081

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 501-515, 2024

Authors: Zhu, Shouxi | Chen, Jian

Article Type: Research Article

Abstract: OBJECTIVE: To study the personality changes of Chinese airline transport pilots in the training process from cadets to captains. METHODS: In This paper, we used the Cattell 16 Personality Factor Questionnaire (16PF) to track and record the personality traits of 200 students majoring in flight technology and 200 “college graduates to pilot” in five different periods from the beginning of aviation theory training to becoming captains. RESULTS: Before the aviation theory training, for the 16 factors of 16PF, there was a significant difference in 11 factors (including Warmth (A), Reasoning (B), etc.) between …the students majoring in flight technology and “college graduates to pilot” (p < 0.05). After the completion of theory training, there were only four factors (Sensitivity (I), Openness to Change (Q1), Self Reliance (Q2) and Perfectionism (Q3) (p < 0.05) between the students majoring in flight technology and “college graduates to pilot”, then after the flight training, there is no significant difference between them. When they became captains, compared with when they were flying cadets, 13 factors of students majoring in flight technology and 7 factors of “college graduates to pilot” had changed significantly. From the perspective of the growth of flying cadets, in the process of becoming a captain, there are three stages that have a great influence on the personality of the participants. The first stage is the university study. The second stage is the flight training, and the third stage is the copilot growing into a captain. CONCLUSION: During the process of a pilot growing from a cadet to a captain, his or her personality is constantly developing and changing, and on the whole, develops towards a personality direction conducive to flight safety. In particular, when a copilot grows into a captain, the personality traits of a qualified airline pilot, including Emotional Stablity (C), Rule-Consciousness (G), Social Boldness (H), Privateness (N), Self-Reliance (Q2), etc., have been greatly strengthened at this stage. Show more

Keywords: Airline transport pilot, flight skills, 16PF, personality, flight training

DOI: 10.3233/JCM237079

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 517-530, 2024

Authors: Liu, Jingyang

Article Type: Research Article

Abstract: At present, private education plays an important role in China’s education system, but there are a series of problems and challenges in the management of private education. The purpose of this study is to discuss and solve the problems existing in the management of private education through the method of fuzzy logic system. Firstly, the application of fuzzy logic systems in related fields is reviewed to understand the potential and advantages of fuzzy logic systems. Then, through the analysis of the main problems in the management of private education, the root of these problems and their impact on the education …system are revealed. By establishing a private education management model based on fuzzy logic system, the application and function of this model in problem analysis and decision making are demonstrated. In the analysis of the results, the accuracy and effectiveness of the fuzzy logic system in the management of private education are evaluated, and the targeted management strategies and countermeasures are put forward to solve the problems in the management of private education. Show more

Keywords: Fuzzy logic system, administration of non-governmental education, decision making, management strategy

DOI: 10.3233/JCM-237043

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 531-546, 2024

Authors: Wu, Xiaoyan | Wang, Shu

Article Type: Research Article

Abstract: In this paper, to solve the current problems of water quality pollution of rivers, such as multiple types, high toxicity and difficult degradation, we design an intelligent surface mobile robot based on the slow release of microorganisms. In the robot, the skeleton has a ship-type structure welded with stainless steel equilateral angle steel; the function module comprises a power supply part, motor part, transmission part, and release part; the wireless monitoring module is based on GPRS and EtherCAT networking technologies and consists of four submodules, including a data acquisition submodule, transmission submodule, database server and monitoring center. The field test …results show stable overall transmission performance and wireless data transmission performance of the robot. When the water depth of the rotating cylinder is 0.3 m, and the speed of the rotating cylinder is 15 r/min, the pollution control ability of the robot is outstanding. The experimental results also verify the feasibility of the robot in treating water pollution. The robot can greatly improve the mechanization, automation and efficiency of water pollution control and facilitate the centralized monitoring of joint operations, so it is worth popularizing. Show more

Keywords: Microorganism, intelligence, robot, wireless motoring, experiment

DOI: 10.3233/JCM-226988

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 547-557, 2024

Authors: Wang, Xiaocun | Xu, Yanjun | Ji, Chenlan | Su, Yun

Article Type: Research Article

Abstract: With the rapid development of microgrid in the electric power industry, the microgrid electric energy transaction has begun to be marketized, and the research on the microgrid electric energy trusted transaction has important theoretical research value and social value. The existing blockchain-based microgrid electric energy trusted transaction models mostly focus on energy management and scheduling control between microgrids when conducting electric energy transactions, and do not fully consider the bidding problems in the market-based transaction of microgrid electric energy, resulting in trading strategies are difficult to adapt to new market changes. In response to this problem, this paper proposes a …reliable transaction approach for microgrid electric energy based on a continuous two-way auction mechanism. The proposed strategy accounts for the volatility of electricity prices in the microgrid trading market and employs the continuous two-way auction mechanism to evaluate the microgrid electricity trading tactics. In the microgrid electric energy transaction, the self-adaptive learning theory is applied to adjust the quotations of both parties, so that both parties can make reasonable quotations according to the market environment. By simulating experimental data, the findings indicate that the continuous two-way auction mechanism transaction strategy enables both parties to modify their quotations based on market transaction information, thereby displaying a high degree of flexibility in microgrid electricity’s market-oriented trading. Show more

Keywords: Component, electric power industry, blockchain-based, trusted transaction strategy, continuous two-way auction

DOI: 10.3233/JCM-226984

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 559-566, 2024

Authors: Lin, Zhuo | Song, Jinling | Kang, Yan | Huang, Da | Zhu, Meining

Article Type: Research Article

Abstract: Remote sensing inversion technology can be used for water quality parameter inversion to realize water quality monitoring in large scale space. The current research on water quality parameter inversion is only for a single satellite. In order to make full use of satellite image resources, the remote sensing images of GF-1B\ C\ D satellite group are taken as the research object. The Mulan River is taken as the research area. The linear regression method is used to construct the regression equations of total phosphorus and ammonia nitrogen, and the inversion model of total phosphorus and ammonia …nitrogen is determined according the evaluation parameters. The MSE of the total phosphorus inversion model is 0.049, and the correlation between the inversion value and the measured value is 0.701. The MSE of the ammonia nitrogen inversion model is 0.063, and the correlation between the inversion value and the measured value is 0.813. These data show that the inversion effect is good. The inversion models are applied to the GF-1D satellite remote sensing image on March 15, 2021 to obtain the large-scale spatial distribution maps of total phosphorus concentration and ammonia nitrogen concentration. The water quality classification maps of the the Mulan River in Putian urban area are obtained too, which are convenient for further analysis and evaluation of the water quality. Show more

Keywords: Satellite group, remote sensing image, water quality parameters, inversion model, linear regression

DOI: 10.3233/JCM226970

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 567-576, 2024

Authors: Yang, Liang | Wang, Youlong | Chen, Yongyue

Article Type: Research Article

Abstract: Due to the advantages of flame cutting in thick plate cutting and cutting cost, it is widely used in the metal cutting process of shipbuilding and machinery manufacturing. But at the same time, the local heating of flame cutting will cause residual stress inside the steel plate. Residual stress is an important reason for deformation and cracking of components. The change of temperature field is the premise of affecting the distribution of residual stress. Cutting speed has an important effect on the distribution of temperature field and residual stress field. In this paper, ABAQUS is used to create a finite …element model for flat flame cutting of Q345D low-alloy steel. Based on the working principle of flame cutting, the model of flame cutting composite heat source is established and the subprogram of composite heat source is written. The thermal-mechanical direct coupling method is used to simulate and analyze the effect of different cutting speeds on the temperature and residual stress field distribution of the flat flame cutting process, to provide a reference for the subsequent processing. Show more

Keywords: Flame cutting, numerical simulation, cutting speed, temperature field, residual stress

DOI: 10.3233/JCM-226976

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 577-593, 2024

Authors: Lin, Shixian | Liao, Weiqiang

Article Type: Research Article

Abstract: This paper proposes a photovoltaic (PV) dynamic maximum power point tracking algorithm based on improved PSO (particle swarm optimization) optimization in response to the problems associated with low tracking accuracy, poor immunity, and the ease of falling into local optimization, as well as the failure of the traditional MPPT algorithm (maximum power point tracking algorithm) under partial shading conditions. Firstly, three traditional MPPT algorithms are compared and analyzed, followed by simulation testing under standard and partial shading conditions. The advantages and disadvantages of three traditional algorithms are analyzed. Secondly, it is proposed that dynamic inertia weights and learning factors be …applied synchronously during the optimization process in order to speed up the tracking speed of particle swarm optimization. In order to evaluate the effectiveness of different algorithms, it is best to simulate them under static and dynamic conditions. In comparison to the standard particle swarm algorithm and three other traditional algorithms, the proposed algorithm is capable of tracking the maximum power point quickly and accurately under conditions of uniform illumination and static and dynamic partial shading. There is a faster convergence speed as well as a greater degree of accuracy at steady state. Show more

Keywords: Photovoltaic, dynamic MPPT algorithm, PSO, optimization

DOI: 10.3233/JCM-226982

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 595-609, 2024

Authors: Wang, Jing

Article Type: Research Article

Abstract: With the rapid development of information technology, the application of e-commerce in small and medium-sized enterprises is becoming more and more extensive. E-commerce is a development direction, not a simple transaction method. E-commerce is widely used in financial, service, and retail industries. The addition of e-commerce has promoted the transformation of these industries to informationization. This study uses the analytical capabilities of artificial intelligence to analyze the utilization rate of e-commerce in smes. The article and research ideas are firstly using artificial intelligence to build an analysis model, and secondly, using the results of model analysis to explore the utilization …rate of e-commerce in small and medium-sized enterprises. Finally, according to the current situation of e-commerce utilization rate of small and medium-sized enterprises, relevant growth strategies are put forward. This paper builds an e-commerce application analysis model based on artificial intelligence technology. After multi-layer verification, the model has good performance in theory and practice. Using this model to analyze the application rate of e-commerce in small and medium-sized enterprises, we can find that there are still the following problems in the application of e-commerce in small and medium-sized enterprises. (1) Lack of experience and lack of guiding standards (2) Lack of reasonable business strategies (3) Lack of offline interaction with users. In order to solve these problems, small and medium-sized enterprises should (1) strengthen publicity and innovation and promote brand marketing (2) strengthen the cultivation and construction of talents (3) optimize the industrial model and reduce industrial costs (4) improve the industrial model and marketing of e-commerce system. Show more

Keywords: Artificial intelligence, smes, e-commerce, utilization rate, growth strategy

DOI: 10.3233/JCM-226933

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 611-621, 2024