Xiaoyuan Wang, Hongfei Wang, Jianping Wang, Jiajia Wang
In this study, the authors perform slant correction on fixed-format dial images using the Hough transform, followed by their “scaling” using binary wavelets to achieve coarse segmentation for characters or numbers. Simultaneously, they propose a binary threshold iteration method that accurately determines the position of each character or number even in the presence of adhesion or fragmentation, enabling precise segmentation. They employ their proposed approach to segment digits and characters displayed on 98 fixed-format dials. Experimental results demonstrate a recognition rate of 98.5% for both letters and numbers, highlighting significant practical value and real-world implications.
{"title":"Research on Machine Instrument Panel Digit Character Segmentation","authors":"Xiaoyuan Wang, Hongfei Wang, Jianping Wang, Jiajia Wang","doi":"10.4018/ijitsa.335941","DOIUrl":"https://doi.org/10.4018/ijitsa.335941","url":null,"abstract":"In this study, the authors perform slant correction on fixed-format dial images using the Hough transform, followed by their “scaling” using binary wavelets to achieve coarse segmentation for characters or numbers. Simultaneously, they propose a binary threshold iteration method that accurately determines the position of each character or number even in the presence of adhesion or fragmentation, enabling precise segmentation. They employ their proposed approach to segment digits and characters displayed on 98 fixed-format dials. Experimental results demonstrate a recognition rate of 98.5% for both letters and numbers, highlighting significant practical value and real-world implications.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"32 11","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139441530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, the increasing use of online surveys for course evaluation in schools has led to an outpouring of evaluation texts. These texts, with their emotional polarity, can give schools the most direct feedback. Emotional analysis on course evaluation, therefore, has great implications. However, the not-so-rigid text grammar and rich text content pose a challenge for sentiment analysis in Chinese course evaluation. To solve this problem, this paper proposes a sentiment classification model BiLSTM-GCN-Att (BGAN). Here, BiLSTM is used to extract the features of the text and output the hidden state vector. Then, the deep biaffine attention mechanism is used to analyze the dependence of the text and generate a dependency matrix. Next, input the hidden state vector to the GCN. Finally, the softmax function is used as the output layer of the model to perform sentiment classification. The model proves effective and experimental results, showing that the BGAN achieved a maximum improvement of 11.02% and 14.47% in precision and F1-score respectively compared with the classical models.
{"title":"A GCN- and Deep Biaffine Attention-Based Classification Model for Course Review Sentiment","authors":"Jiajia Jiao, Bo Chen","doi":"10.4018/ijitsa.323568","DOIUrl":"https://doi.org/10.4018/ijitsa.323568","url":null,"abstract":"In recent years, the increasing use of online surveys for course evaluation in schools has led to an outpouring of evaluation texts. These texts, with their emotional polarity, can give schools the most direct feedback. Emotional analysis on course evaluation, therefore, has great implications. However, the not-so-rigid text grammar and rich text content pose a challenge for sentiment analysis in Chinese course evaluation. To solve this problem, this paper proposes a sentiment classification model BiLSTM-GCN-Att (BGAN). Here, BiLSTM is used to extract the features of the text and output the hidden state vector. Then, the deep biaffine attention mechanism is used to analyze the dependence of the text and generate a dependency matrix. Next, input the hidden state vector to the GCN. Finally, the softmax function is used as the output layer of the model to perform sentiment classification. The model proves effective and experimental results, showing that the BGAN achieved a maximum improvement of 11.02% and 14.47% in precision and F1-score respectively compared with the classical models.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"357 9","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138625773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tianlong Wang, Chaoyang Wang, Zhiqiang Liu, Shuai Ma, Huibo Yan
During the deep peak shaving period, the boiler needs to operate at a lower load, so higher requirements were set for the boiler's stable combustion. In order to better evaluate and compare the stable ignition capacity of bluff-body burners and slotted bluff-body burners, guidance and calculation support for the design of boiler deep peak shaving were needed. This study adopted the reflux heating chain ignition analysis method to study the differences in the steady combustion mechanism between the bluff-body burner and the slotted bluff-body burner. A thermal combustion experiment was conducted in employing the single angle coal powder combustion furnace. The experimental results were compared against the theoretical analysis results. In addition, a study was conducted on the application of slotted bluff-body burners in the deep peak shaving of a 330MW unit power plant boiler. The results showed that as long as the small slot flow can catch fire, the mixed temperature of the reflux fluid of the slotted bluff-body burner will be higher than that of the bluff body burner. This will enhance its steady combustion ability. The combustion test results were found to be consistent with the analysis results, indicating that when the slotted bluff-body burner is used on the 330MW unit, the boiler combustion is in good condition. In this case, it has a stable combustion capacity of 66MW (20% economic continuous rating) without oil injection at low loads. This study revealed the advantages of the slotted bluff-body burner in terms of its steady combustion mechanism compared to traditional bluff-body burners. It verified the feasibility for boiler deep peak shaving in practical applications. This is of great significance for improving the flexibility of coal-fired power generation units, enhancing the flexibility of the power system, and promoting carbon reduction.
{"title":"Experiment Study and Industrial Application of Slotted Bluff-Body Burner Applied to Deep Peak Regulation","authors":"Tianlong Wang, Chaoyang Wang, Zhiqiang Liu, Shuai Ma, Huibo Yan","doi":"10.4018/ijitsa.332411","DOIUrl":"https://doi.org/10.4018/ijitsa.332411","url":null,"abstract":"During the deep peak shaving period, the boiler needs to operate at a lower load, so higher requirements were set for the boiler's stable combustion. In order to better evaluate and compare the stable ignition capacity of bluff-body burners and slotted bluff-body burners, guidance and calculation support for the design of boiler deep peak shaving were needed. This study adopted the reflux heating chain ignition analysis method to study the differences in the steady combustion mechanism between the bluff-body burner and the slotted bluff-body burner. A thermal combustion experiment was conducted in employing the single angle coal powder combustion furnace. The experimental results were compared against the theoretical analysis results. In addition, a study was conducted on the application of slotted bluff-body burners in the deep peak shaving of a 330MW unit power plant boiler. The results showed that as long as the small slot flow can catch fire, the mixed temperature of the reflux fluid of the slotted bluff-body burner will be higher than that of the bluff body burner. This will enhance its steady combustion ability. The combustion test results were found to be consistent with the analysis results, indicating that when the slotted bluff-body burner is used on the 330MW unit, the boiler combustion is in good condition. In this case, it has a stable combustion capacity of 66MW (20% economic continuous rating) without oil injection at low loads. This study revealed the advantages of the slotted bluff-body burner in terms of its steady combustion mechanism compared to traditional bluff-body burners. It verified the feasibility for boiler deep peak shaving in practical applications. This is of great significance for improving the flexibility of coal-fired power generation units, enhancing the flexibility of the power system, and promoting carbon reduction.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135168493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To improve transportation efficiency, this paper analyzes the factors of transportation structure from the two levels of transportation—input and system output. An epsilon-based measure model of non-expected output is introduced, and the environmental benefits of transportation are considered. This model is used to analyze the regional transportation efficiency of 30 provinces and cities in China. Tobit regression and geographically weighted regression are applied to analyze the causes and spatial variation of differences in the efficiency of the transportation structure, and corresponding structural adjustment strategies are proposed. The results show that the regression coefficients of the share of secondary industry output in GDP, population density, and social fixed asset investment exert the most significant effects on transportation structure efficiency. The spatial distribution of sub-variable coefficients shows that spatial heterogeneity exists in the degree of influence of various socio-economic factors on the transportation structure efficiency in different regions.
{"title":"Estimation and Convergence Analysis of Traffic Structure Efficiency Based on an Undesirable Epsilon-Based Measure Model","authors":"Xudong Cao, Chenchen Chen, Lejia Zhang, Li Pan","doi":"10.4018/ijitsa.332798","DOIUrl":"https://doi.org/10.4018/ijitsa.332798","url":null,"abstract":"To improve transportation efficiency, this paper analyzes the factors of transportation structure from the two levels of transportation—input and system output. An epsilon-based measure model of non-expected output is introduced, and the environmental benefits of transportation are considered. This model is used to analyze the regional transportation efficiency of 30 provinces and cities in China. Tobit regression and geographically weighted regression are applied to analyze the causes and spatial variation of differences in the efficiency of the transportation structure, and corresponding structural adjustment strategies are proposed. The results show that the regression coefficients of the share of secondary industry output in GDP, population density, and social fixed asset investment exert the most significant effects on transportation structure efficiency. The spatial distribution of sub-variable coefficients shows that spatial heterogeneity exists in the degree of influence of various socio-economic factors on the transportation structure efficiency in different regions.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"BME-34 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135167371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the promotion of the new round of industrial revolution, the development environment of enterprises has undergone tremendous changes. Collaboration among enterprises has become crucial for enhancing core competitiveness, with the concept of the supply chain playing a key role. However, the complex and vulnerable nature of the supply chain operation environment poses various risks, hampering effective cooperative relationships between enterprises. This article proposed integrating the partial least-squares-artificial neural network (PLS-ANN) method to address this issue and optimize collaborative enterprise practices. The study examined enterprise collaboration optimization. This article uses used artificial neural network (ANN) to classify various complex data, implement an intelligent algorithm model for synchronous processing, and combine partial least squares (PLS) to classify and process the data information generated by collaborative networks to find the best match, minimizing the negative impact of multiple correlations of variables on enterprise collaboration. An empirical analysis was conducted in 2022, focusing on a manufacturing enterprise's supply chain and external cooperation management. The analysis examined two aspects: the supply chain's risk resistance level and the effectiveness of enterprise cooperation. Results showed that after implementing the PLS-ANN model, the average trust index between the enterprise and eight cooperative partners increased to approximately 0.652, compared to the initial average trust index of only 0.528. Detailed data analysis indicated that the PLS-ANN method effectively improved the supply chain's risk resistance capability while optimizing the cooperative relationships among all participating enterprises.
{"title":"Enterprise Collaboration Optimization in China Based on Supply Chain Resilience Enhancement","authors":"Minyan Jin","doi":"10.4018/ijitsa.331400","DOIUrl":"https://doi.org/10.4018/ijitsa.331400","url":null,"abstract":"With the promotion of the new round of industrial revolution, the development environment of enterprises has undergone tremendous changes. Collaboration among enterprises has become crucial for enhancing core competitiveness, with the concept of the supply chain playing a key role. However, the complex and vulnerable nature of the supply chain operation environment poses various risks, hampering effective cooperative relationships between enterprises. This article proposed integrating the partial least-squares-artificial neural network (PLS-ANN) method to address this issue and optimize collaborative enterprise practices. The study examined enterprise collaboration optimization. This article uses used artificial neural network (ANN) to classify various complex data, implement an intelligent algorithm model for synchronous processing, and combine partial least squares (PLS) to classify and process the data information generated by collaborative networks to find the best match, minimizing the negative impact of multiple correlations of variables on enterprise collaboration. An empirical analysis was conducted in 2022, focusing on a manufacturing enterprise's supply chain and external cooperation management. The analysis examined two aspects: the supply chain's risk resistance level and the effectiveness of enterprise cooperation. Results showed that after implementing the PLS-ANN model, the average trust index between the enterprise and eight cooperative partners increased to approximately 0.652, compared to the initial average trust index of only 0.528. Detailed data analysis indicated that the PLS-ANN method effectively improved the supply chain's risk resistance capability while optimizing the cooperative relationships among all participating enterprises.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135047432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The intelligent lighting control system will unify the management of lighting equipment in outpatient buildings, inpatient buildings, and other buildings of the hospital, thereby improving the service quality of the hospital, providing a comfortable and relaxed working environment for medical staff, and providing a warm and comfortable treatment environment for patients. This project aims to develop a health rehabilitation environment lighting automation control system based on combining Zigbee Wide Ad Hoc Network and RFID (Radio Frequency Identification) technology. It can be customized according to the comfort needs of patients and can achieve lighting adjustments before the patient arrives. A PSO-based intelligent lighting control method has been proposed. To overcome the shortcomings of PSO such as being prone to local minima and premature convergence, a new PSO optimization method is proposed based on the inertia weight PSO and combined with genetic optimization theory. This method can not only learn experience from individuals in the group but also avoid the possibility of parent particles falling into local extremum. Compared with the original particle swarm optimization algorithm, the new particle swarm optimization algorithm can quickly find the optimal combination of lighting devices, improve computational efficiency by 6.208%, and also reduce the energy consumption of the calculated lighting devices, indicating the advantages of the new particle swarm optimization algorithm.
智能照明控制系统将统一医院门诊楼、住院楼及其他建筑的照明设备管理，从而提高医院的服务质量，为医护人员提供舒适轻松的工作环境，为患者提供温馨舒适的治疗环境。本项目旨在开发基于Zigbee Wide Ad Hoc Network和RFID(无线射频识别)技术相结合的健康康复环境照明自动化控制系统。它可以根据患者的舒适度需求进行定制，并可以在患者到达之前实现灯光调节。提出了一种基于粒子群算法的智能照明控制方法。针对粒子群算法容易出现局部极小和过早收敛的缺点，提出了一种基于惯性权值粒子群算法并结合遗传优化理论的粒子群优化方法。这种方法既可以从群体中个体学习经验，又可以避免母粒子陷入局部极值的可能性。与原有的粒子群优化算法相比，新的粒子群优化算法可以快速找到照明器件的最优组合，计算效率提高了6.208%，同时也降低了计算照明器件的能耗，表明了新粒子群优化算法的优势。
{"title":"Design of Health Healing Lighting in a Medical Center Based on Intelligent Lighting Control System","authors":"Yan Huang, Minmin Li","doi":"10.4018/ijitsa.331399","DOIUrl":"https://doi.org/10.4018/ijitsa.331399","url":null,"abstract":"The intelligent lighting control system will unify the management of lighting equipment in outpatient buildings, inpatient buildings, and other buildings of the hospital, thereby improving the service quality of the hospital, providing a comfortable and relaxed working environment for medical staff, and providing a warm and comfortable treatment environment for patients. This project aims to develop a health rehabilitation environment lighting automation control system based on combining Zigbee Wide Ad Hoc Network and RFID (Radio Frequency Identification) technology. It can be customized according to the comfort needs of patients and can achieve lighting adjustments before the patient arrives. A PSO-based intelligent lighting control method has been proposed. To overcome the shortcomings of PSO such as being prone to local minima and premature convergence, a new PSO optimization method is proposed based on the inertia weight PSO and combined with genetic optimization theory. This method can not only learn experience from individuals in the group but also avoid the possibility of parent particles falling into local extremum. Compared with the original particle swarm optimization algorithm, the new particle swarm optimization algorithm can quickly find the optimal combination of lighting devices, improve computational efficiency by 6.208%, and also reduce the energy consumption of the calculated lighting devices, indicating the advantages of the new particle swarm optimization algorithm.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135828217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yang Yubo, Meng Jing, Duan Xiaomeng, Bai Jingfen, Jin Yang
This article proposes a multisource heterogeneous experimental data recognition method based on CRNN and DBNet in a cloud-edge collaborative environment in an attempt to address the issues of low efficiency and a high error rate that come with traditional manual data detection and recognition. Firstly, a recognition architecture for experimental detection data of intelligent measurement systems is designed based on a cloud-edge collaborative environment to improve the efficiency of data processing. Then, the improved DBNet network is used in the edge computing center to detect the text, and the correction module is used to correct the deviation of the detected text to ensure the standardization of the text. Finally, in the central cloud, the end-to-end indefinite length character recognition (CRNN) algorithm is used to analyze and identify the text order, rules, and other information of the image after the correction is completed, extract the test detection data, and convert the detection data into row data according to the two-dimensional table structure, and conduct structured storage and management through the relational database. An experimental analysis of the proposed method is conducted based on the deep learning framework, and results show that its accuracy rate and recall rate are close to 96% and 94%, respectively, with an average accuracy of 95.09%. This fully demonstrates the proposed method is effective and, therefore, applicable to power equipment experimental detection data recognition.
{"title":"Data Recognition for Multi-Source Heterogeneous Experimental Detection in Cloud Edge Collaboratives","authors":"Yang Yubo, Meng Jing, Duan Xiaomeng, Bai Jingfen, Jin Yang","doi":"10.4018/ijitsa.330986","DOIUrl":"https://doi.org/10.4018/ijitsa.330986","url":null,"abstract":"This article proposes a multisource heterogeneous experimental data recognition method based on CRNN and DBNet in a cloud-edge collaborative environment in an attempt to address the issues of low efficiency and a high error rate that come with traditional manual data detection and recognition. Firstly, a recognition architecture for experimental detection data of intelligent measurement systems is designed based on a cloud-edge collaborative environment to improve the efficiency of data processing. Then, the improved DBNet network is used in the edge computing center to detect the text, and the correction module is used to correct the deviation of the detected text to ensure the standardization of the text. Finally, in the central cloud, the end-to-end indefinite length character recognition (CRNN) algorithm is used to analyze and identify the text order, rules, and other information of the image after the correction is completed, extract the test detection data, and convert the detection data into row data according to the two-dimensional table structure, and conduct structured storage and management through the relational database. An experimental analysis of the proposed method is conducted based on the deep learning framework, and results show that its accuracy rate and recall rate are close to 96% and 94%, respectively, with an average accuracy of 95.09%. This fully demonstrates the proposed method is effective and, therefore, applicable to power equipment experimental detection data recognition.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134885252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The demand for power exchange has risen dramatically as the number of electric vehicle (EV) users has increased, and large-scale disorderly charging will increase the operating costs of battery swapping stations and increase the risk to the power grid. Through experimental comparison with other algorithms on 23 test functions, the results demonstrate that the convergence accuracy and speed of this improved algorithm are superior to those of other algorithms. Furthermore, in solving the optimization problem of EV battery swapping station scheduling, by reasonably allocating the battery pack charging time and establishing the forecasting model of switching demand, the average variance and peak-to-average ratio of the grid are reduced by 29.55% and 13.2%, respectively, based on meeting the user's switching demand. Approximately a 12,500 RMB reduction in the cost of charging lowers the operation cost and risk of battery swapping stations and enhances the user experience.
{"title":"Application of Improved Sparrow Search Algorithm in Electric Battery Swapping Station Switching Dispatching","authors":"Qingsheng Shi, Feifan Zhao","doi":"10.4018/ijitsa.330421","DOIUrl":"https://doi.org/10.4018/ijitsa.330421","url":null,"abstract":"The demand for power exchange has risen dramatically as the number of electric vehicle (EV) users has increased, and large-scale disorderly charging will increase the operating costs of battery swapping stations and increase the risk to the power grid. Through experimental comparison with other algorithms on 23 test functions, the results demonstrate that the convergence accuracy and speed of this improved algorithm are superior to those of other algorithms. Furthermore, in solving the optimization problem of EV battery swapping station scheduling, by reasonably allocating the battery pack charging time and establishing the forecasting model of switching demand, the average variance and peak-to-average ratio of the grid are reduced by 29.55% and 13.2%, respectively, based on meeting the user's switching demand. Approximately a 12,500 RMB reduction in the cost of charging lowers the operation cost and risk of battery swapping stations and enhances the user experience.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136130946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A 3D simulation model of dry-type air core reactors is established through the multi-physical-field coupling method based on an electromagnetic-temperature-structural field, and the electromagnetic distribution characteristics, temperature, and structural deformation of the reactor are analyzed. The inductance, temperature rise, structural deformation, and amount of metal conductors of the reactor are the optimization parameters. Initially, the sample data was obtained through the orthogonal test method and multi-physical-field coupling simulation; then, the VIKOR (Vise Kriterijumski Optimizacioni Racun) method was used to equalize and control the electromagnetism, temperature rise, structural deformation, and metal conductor consumption of the reactor. Finally, multi-physical-field coupling technique is used to verify the correctness of the method. The results show that the inductance deviation of the optimized reactor is 4.51%, the highest temperature and the maximum deformation of the encapsulation coil are reduced by 13.5% and 0.52%, and the metal conductor mass of the coil increases by 7.57%, which meet the design requirements.
{"title":"Optimized Design Method of Dry Type Air Core Reactor Based on Multi-Physical Field Coupling","authors":"Xiangyu Li, Xunwei Zhao","doi":"10.4018/ijitsa.330248","DOIUrl":"https://doi.org/10.4018/ijitsa.330248","url":null,"abstract":"A 3D simulation model of dry-type air core reactors is established through the multi-physical-field coupling method based on an electromagnetic-temperature-structural field, and the electromagnetic distribution characteristics, temperature, and structural deformation of the reactor are analyzed. The inductance, temperature rise, structural deformation, and amount of metal conductors of the reactor are the optimization parameters. Initially, the sample data was obtained through the orthogonal test method and multi-physical-field coupling simulation; then, the VIKOR (Vise Kriterijumski Optimizacioni Racun) method was used to equalize and control the electromagnetism, temperature rise, structural deformation, and metal conductor consumption of the reactor. Finally, multi-physical-field coupling technique is used to verify the correctness of the method. The results show that the inductance deviation of the optimized reactor is 4.51%, the highest temperature and the maximum deformation of the encapsulation coil are reduced by 13.5% and 0.52%, and the metal conductor mass of the coil increases by 7.57%, which meet the design requirements.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135153130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The building envelope structure is the cause of a major part of energy consumption, with exterior walls and windows being the main energy-consuming components. Traditional building energy conservation measures often overlook the demand for human comfort, especially in areas characterized by hot summers and warm winters. For this paper, the authors concentrated on indoor comfort, with a focus on optimizing the heat transfer coefficient of windows and exterior walls using a genetic algorithm. They used a genetic algorithm to explore the performance optimization of exterior walls and windows in the enclosure structure. To aid this effort, they constructed a building energy-saving optimization model. In addition, they created an optimization model in an attempt to reduce building energy consumption. They took the heat transfer coefficients of the outer window and the outer wall as the optimization parameters of the established model, and they compiled the optimization program using MATLAB. The experimental results showed that the heat transfer coefficients of exterior walls and windows in cold regions are 0.4459 and 2.7875, respectively, while the heat transfer coefficients in warm winter and hot summer regions are 0.66, 1.98, 1.026, and 1.59. The conducted work provides a reference for the optimization design of the heat transfer coefficient of external walls and windows as a measure to enhance building energy efficiency.
{"title":"Construction of Building an Energy Saving Optimization Model Based on Genetic Algorithm","authors":"Xin Xu, Xiaolong Li","doi":"10.4018/ijitsa.328758","DOIUrl":"https://doi.org/10.4018/ijitsa.328758","url":null,"abstract":"The building envelope structure is the cause of a major part of energy consumption, with exterior walls and windows being the main energy-consuming components. Traditional building energy conservation measures often overlook the demand for human comfort, especially in areas characterized by hot summers and warm winters. For this paper, the authors concentrated on indoor comfort, with a focus on optimizing the heat transfer coefficient of windows and exterior walls using a genetic algorithm. They used a genetic algorithm to explore the performance optimization of exterior walls and windows in the enclosure structure. To aid this effort, they constructed a building energy-saving optimization model. In addition, they created an optimization model in an attempt to reduce building energy consumption. They took the heat transfer coefficients of the outer window and the outer wall as the optimization parameters of the established model, and they compiled the optimization program using MATLAB. The experimental results showed that the heat transfer coefficients of exterior walls and windows in cold regions are 0.4459 and 2.7875, respectively, while the heat transfer coefficients in warm winter and hot summer regions are 0.66, 1.98, 1.026, and 1.59. The conducted work provides a reference for the optimization design of the heat transfer coefficient of external walls and windows as a measure to enhance building energy efficiency.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46097261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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