With the rapid increase in the number of electric vehicles (EVs), vehicle-to-grid (V2G) technology plays a vital role in reducing the burden on the power system. This technology optimizes network load distribution through a two-way charging mechanism and effectively alleviates network load fluctuations. However, potential negative impacts on EV battery life should also be a cause for concern. Furthermore, the technology does not fundamentally change the charging behavior of electric vehicles. Against this background, this study proposes a multi-objective optimization strategy to adapt electricity price policy to network load fluctuations to control charging behavior. This strategy optimizes battery attenuation, charging costs, and network load fluctuations, aiming to alleviate network load fluctuations while completely solving user concerns about charging and battery maintenance costs. Simulation analysis has verified the effectiveness of this model in reducing grid load fluctuations and balancing user costs.
{"title":"Bi-Directional Optimization of V2G Strategy Based on Multi-Objective Optimization: Balancing Grid Load and Reducing Electric Vehicle Charging Costs","authors":"Yilin Liu","doi":"10.61173/75xhcx48","DOIUrl":"https://doi.org/10.61173/75xhcx48","url":null,"abstract":"With the rapid increase in the number of electric vehicles (EVs), vehicle-to-grid (V2G) technology plays a vital role in reducing the burden on the power system. This technology optimizes network load distribution through a two-way charging mechanism and effectively alleviates network load fluctuations. However, potential negative impacts on EV battery life should also be a cause for concern. Furthermore, the technology does not fundamentally change the charging behavior of electric vehicles. Against this background, this study proposes a multi-objective optimization strategy to adapt electricity price policy to network load fluctuations to control charging behavior. This strategy optimizes battery attenuation, charging costs, and network load fluctuations, aiming to alleviate network load fluctuations while completely solving user concerns about charging and battery maintenance costs. Simulation analysis has verified the effectiveness of this model in reducing grid load fluctuations and balancing user costs.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"343 6‐7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381051","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}
This article analyzes the impact of housing satisfaction from multiple perspectives. And there are no missing values in the data. Factor analysis is used to reduce the dimensionality of variables, integrating multiple factors into five factors for easy analysis. The meanings of the factors are clear, namely: living conditions, family situation, regional economy, experience situation, and social employment quality. The factor is processed using binomial logistic regression, and the prediction effect is relatively satisfactory. Analysis of the parameters shows that the better the current living conditions, the higher the regional economy, the higher the quality of social employment, and the higher the probability of housing satisfaction. By comparing the full variable binomial logistic regression, it was found that the older the model parameters, the better their age and employment status, the larger their per capita living area, and the lower their education level. Unmarried individuals are more likely to be satisfied with their houses, which is consistent with basic knowledge.
{"title":"Research on the Influencing Factors of Housing Satisfaction","authors":"Maimu Yang","doi":"10.61173/p3g1ht41","DOIUrl":"https://doi.org/10.61173/p3g1ht41","url":null,"abstract":"This article analyzes the impact of housing satisfaction from multiple perspectives. And there are no missing values in the data. Factor analysis is used to reduce the dimensionality of variables, integrating multiple factors into five factors for easy analysis. The meanings of the factors are clear, namely: living conditions, family situation, regional economy, experience situation, and social employment quality. The factor is processed using binomial logistic regression, and the prediction effect is relatively satisfactory. Analysis of the parameters shows that the better the current living conditions, the higher the regional economy, the higher the quality of social employment, and the higher the probability of housing satisfaction. By comparing the full variable binomial logistic regression, it was found that the older the model parameters, the better their age and employment status, the larger their per capita living area, and the lower their education level. Unmarried individuals are more likely to be satisfied with their houses, which is consistent with basic knowledge.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"23 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379091","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}
Multiple regression analysis is a statistical method used to examine the relationship between a dependent variable and multiple independent variables. It extends the principles of simple linear regression to accommodate the complexity of real-world data, allowing researchers to study the combined effect of multiple predictors on an outcome of interest. This article provides a comprehensive overview of multiple regression analysis, including its theoretical foundations, practical applications, and key considerations. First, we discuss the basic concept of multiple regression and its historical development, tracing its evolution from simple linear regression. The article then delves into the methodology of multiple regression, covering topics such as model specification, estimation techniques, and model evaluation. Additionally, it explores advanced topics in multiple regression analysis, including multicollinearity, heteroskedasticity, and model selection. Real-world examples and case studies from a variety of fields illustrate the versatility and applicability of multiple regression analysis in empirical research. By providing a thorough understanding of multiple regression, this article aims to provide researchers with the knowledge and tools needed to effectively utilize this statistical technique in their own research.
{"title":"Exploring Multiple Regression Models: Key Concepts and Applications","authors":"Yanbo Ruan","doi":"10.61173/yjpt3s59","DOIUrl":"https://doi.org/10.61173/yjpt3s59","url":null,"abstract":"Multiple regression analysis is a statistical method used to examine the relationship between a dependent variable and multiple independent variables. It extends the principles of simple linear regression to accommodate the complexity of real-world data, allowing researchers to study the combined effect of multiple predictors on an outcome of interest. This article provides a comprehensive overview of multiple regression analysis, including its theoretical foundations, practical applications, and key considerations. First, we discuss the basic concept of multiple regression and its historical development, tracing its evolution from simple linear regression. The article then delves into the methodology of multiple regression, covering topics such as model specification, estimation techniques, and model evaluation. Additionally, it explores advanced topics in multiple regression analysis, including multicollinearity, heteroskedasticity, and model selection. Real-world examples and case studies from a variety of fields illustrate the versatility and applicability of multiple regression analysis in empirical research. By providing a thorough understanding of multiple regression, this article aims to provide researchers with the knowledge and tools needed to effectively utilize this statistical technique in their own research.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"1 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379366","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 progress of science and technology, the material life of human society is becoming more and more perfect. Still, it also causes the human living environment to become more and more harsh. Water resources are polluted to different degrees, affecting the sustainable development of ecology. Water resource management based on emerging technologies is urgent. The purpose of this paper is to analyze and evaluate the pollutants and types of pollution in the water body of Poyang Lake based on multi-source remote sensing data through the pollution indicators of colored soluble organic matter pollution, water body eutrophication, and heavy metal salt pollution. This paper concludes that Poyang Lake faces problems such as high organic pollution during the abundant water period, medium eutrophication of the water body, and excessive cadmium and manganese heavy metal salts. This paper finds that establishing relatively different pollution indicator systems is more conducive to analyzing and evaluating water resource pollution in different geographical areas. With the progress of remote sensing science, more and more remote sensing technology is applied to the governance and management process of water resource pollution.
{"title":"Integrating Multi-source Remote Sensing Technology to Improve Water Resource Management Methods at Poyang Lake","authors":"Xinye Chen, Pengcheng Feng, Weijun Feng, Zhuozhuo Shao","doi":"10.61173/ck4av294","DOIUrl":"https://doi.org/10.61173/ck4av294","url":null,"abstract":"With the progress of science and technology, the material life of human society is becoming more and more perfect. Still, it also causes the human living environment to become more and more harsh. Water resources are polluted to different degrees, affecting the sustainable development of ecology. Water resource management based on emerging technologies is urgent. The purpose of this paper is to analyze and evaluate the pollutants and types of pollution in the water body of Poyang Lake based on multi-source remote sensing data through the pollution indicators of colored soluble organic matter pollution, water body eutrophication, and heavy metal salt pollution. This paper concludes that Poyang Lake faces problems such as high organic pollution during the abundant water period, medium eutrophication of the water body, and excessive cadmium and manganese heavy metal salts. This paper finds that establishing relatively different pollution indicator systems is more conducive to analyzing and evaluating water resource pollution in different geographical areas. With the progress of remote sensing science, more and more remote sensing technology is applied to the governance and management process of water resource pollution.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"103 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376812","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 application of UAV remote sensing technology in engineering surveying and mapping has gradually become widespread due to its high efficiency and accuracy. It cannot only quickly obtain high-definition mapping data to provide accurate and complete information support for engineering design and construction but also make up for the limitations of traditional engineering surveying and mapping and promote the innovation and development of the surveying and mapping field. Therefore, this paper explores the application of UAV remote sensing technology in engineering mapping. The exploration of UAV remote sensing technology is of great practical significance for achieving the goal of high-quality mapping data and high efficiency of the mapping process. Surveying and mapping staff need to have a correct perception and logic of the workflow of UAV remote sensing technology in the field of engineering surveying and mapping, analyze the needs of engineering surveying and mapping step by step, study the use of the technology and specific scenes, and promote the rapid development of technology and innovation, to give full play to the role of remote sensing technology of UAVs, and to arrive at more accurate measurement results.
{"title":"Exploration of the Application of UAV Remote Sensing Technology in Engineering Surveying and Mapping","authors":"Suqi Liu","doi":"10.61173/f0qwkj60","DOIUrl":"https://doi.org/10.61173/f0qwkj60","url":null,"abstract":"The application of UAV remote sensing technology in engineering surveying and mapping has gradually become widespread due to its high efficiency and accuracy. It cannot only quickly obtain high-definition mapping data to provide accurate and complete information support for engineering design and construction but also make up for the limitations of traditional engineering surveying and mapping and promote the innovation and development of the surveying and mapping field. Therefore, this paper explores the application of UAV remote sensing technology in engineering mapping. The exploration of UAV remote sensing technology is of great practical significance for achieving the goal of high-quality mapping data and high efficiency of the mapping process. Surveying and mapping staff need to have a correct perception and logic of the workflow of UAV remote sensing technology in the field of engineering surveying and mapping, analyze the needs of engineering surveying and mapping step by step, study the use of the technology and specific scenes, and promote the rapid development of technology and innovation, to give full play to the role of remote sensing technology of UAVs, and to arrive at more accurate measurement results.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"199 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376107","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}
As the primary cause of global warming, the increase in atmospheric carbon dioxide(CO2) concentration has attracted more and more attention worldwide. With the slogan of “peaking carbon” and “carbon neutrality” in China, the need for quantitative, real-time, and large-scale monitoring of CO2 concentration is becoming more urgent. As an all-weather, high-precision monitoring method for greenhouse gas emissions, satellite remote sensing has great potential in CO2 monitoring. After studying the development and performance of remote sensing satellites for CO2 monitoring, the conclusion drawn by this paper is that the monitoring accuracy of CO2 monitoring sensors is gradually improved with increasing attention to CO2 concentration detection in various countries and that because active remote sensing is not affected by aerosol and solar radiation, the current high-precision CO2 concentration detection has gradually changed from passive remote sensing to a combination of active and passive remote sensing. By reviewing the development process of CO2 monitoring remote sensing satellites and the research and application of CO2 satellite data, this paper finds out the gaps in the current research of CO2 remote sensing satellites. It inspires future scholars who want to carry out research in this field.
{"title":"Progress and Case Study of Satellite Remote Rensing Technology for Carbon Dioxide","authors":"Jinbo Pu","doi":"10.61173/k28nqk82","DOIUrl":"https://doi.org/10.61173/k28nqk82","url":null,"abstract":"As the primary cause of global warming, the increase in atmospheric carbon dioxide(CO2) concentration has attracted more and more attention worldwide. With the slogan of “peaking carbon” and “carbon neutrality” in China, the need for quantitative, real-time, and large-scale monitoring of CO2 concentration is becoming more urgent. As an all-weather, high-precision monitoring method for greenhouse gas emissions, satellite remote sensing has great potential in CO2 monitoring. After studying the development and performance of remote sensing satellites for CO2 monitoring, the conclusion drawn by this paper is that the monitoring accuracy of CO2 monitoring sensors is gradually improved with increasing attention to CO2 concentration detection in various countries and that because active remote sensing is not affected by aerosol and solar radiation, the current high-precision CO2 concentration detection has gradually changed from passive remote sensing to a combination of active and passive remote sensing. By reviewing the development process of CO2 monitoring remote sensing satellites and the research and application of CO2 satellite data, this paper finds out the gaps in the current research of CO2 remote sensing satellites. It inspires future scholars who want to carry out research in this field.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"358 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381072","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 the context of the “double carbon” strategy and the rapid development of deep learning, it provides new ideas for load forecasting of intelligent microgrids. In this study, we choose the Informer model based on the Transformer framework, which improves the self-attention mechanism and reduces the computational cost, to improve load accuracy and to achieve intelligent management of the microgrid system by accurately forecasting power load data.
{"title":"Deepening Intelligent Microgrid Management: A Study on Improving Load Forecasting Accuracy Based on Informer Models","authors":"Yuke Wang","doi":"10.61173/sq6kd003","DOIUrl":"https://doi.org/10.61173/sq6kd003","url":null,"abstract":"In the context of the “double carbon” strategy and the rapid development of deep learning, it provides new ideas for load forecasting of intelligent microgrids. In this study, we choose the Informer model based on the Transformer framework, which improves the self-attention mechanism and reduces the computational cost, to improve load accuracy and to achieve intelligent management of the microgrid system by accurately forecasting power load data.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"5 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380678","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, medical waste has gained attention due to its hazardous nature, complexity, and high cost of manual sorting and management. Therefore, it is crucial to develop classification systems that are accurate and efficient. This study analyzes various deep learning models for medical waste classification, compares their accuracies in image recognition, and provides an in-depth analysis of EfficientNet, a classification model that is well-suited to handle large amounts of waste mixing. EfficientNet’s superior performance can be adapted to numerous potential scenarios in medical waste, and its improved performance is also very promising in the field of medical waste classification. The data demonstrate its significant advantages over other models, indicating broad application prospects and economic benefits.
{"title":"Improvement of EfficientNet in medical waste classification","authors":"Xiaomo Wang","doi":"10.61173/dzxz2j87","DOIUrl":"https://doi.org/10.61173/dzxz2j87","url":null,"abstract":"In recent years, medical waste has gained attention due to its hazardous nature, complexity, and high cost of manual sorting and management. Therefore, it is crucial to develop classification systems that are accurate and efficient. This study analyzes various deep learning models for medical waste classification, compares their accuracies in image recognition, and provides an in-depth analysis of EfficientNet, a classification model that is well-suited to handle large amounts of waste mixing. EfficientNet’s superior performance can be adapted to numerous potential scenarios in medical waste, and its improved performance is also very promising in the field of medical waste classification. The data demonstrate its significant advantages over other models, indicating broad application prospects and economic benefits.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"211 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141375971","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}
This article aims to identify those factors that have an impact on new energy vehicle prices. The method of multiple linear regression is used to analyze the significant factors using 100 samples from Kaggle. Based on an assumption, 13 variables that were chosen do correlate with new energy car prices. This paper will analyze these following factors: energy type, engine power, reviews count, seating capacity, fuel tank capacity, body type, rating, no cylinder, max power rp, max power bhp, max power rpm, max power nm, transmission type. This article uses multiple linear regression models to analyze these factors’ influence on new energy vehicles. Overall, new energy vehicle prices can be analyzed by the extent to which these factors affect them. By calculation, it is determined that engine power, no cylinder, and max power bhp will have a significant positive impact on the starting price. Max torque rpm and max torque nm will have a significant negative influence on the starting price.
{"title":"Research on the Influencing Factors of New Energy Cars Prices","authors":"Xijun Wang","doi":"10.61173/qbt0bb62","DOIUrl":"https://doi.org/10.61173/qbt0bb62","url":null,"abstract":"This article aims to identify those factors that have an impact on new energy vehicle prices. The method of multiple linear regression is used to analyze the significant factors using 100 samples from Kaggle. Based on an assumption, 13 variables that were chosen do correlate with new energy car prices. This paper will analyze these following factors: energy type, engine power, reviews count, seating capacity, fuel tank capacity, body type, rating, no cylinder, max power rp, max power bhp, max power rpm, max power nm, transmission type. This article uses multiple linear regression models to analyze these factors’ influence on new energy vehicles. Overall, new energy vehicle prices can be analyzed by the extent to which these factors affect them. By calculation, it is determined that engine power, no cylinder, and max power bhp will have a significant positive impact on the starting price. Max torque rpm and max torque nm will have a significant negative influence on the starting price.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"353 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380656","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}
This paper presents the design of a fire safety and security network for high-rise buildings based on wireless sensor networks. Utilizing the Zigbee system’s topology and Zigbee technology for wireless sensor network communication, the design enables intercommunication among sensor nodes, forming a multi-network system. This system facilitates the preemptive warning and dissemination of fire-related information, facilitating efficient information transmission. Simulation results affirm the practical effectiveness of this design scheme, underscoring its substantial applicability.
{"title":"Research on Fire Alarm Network for High-rise Buildings Based on Wireless Sensor Networks","authors":"Keyan Wei","doi":"10.61173/8m678b18","DOIUrl":"https://doi.org/10.61173/8m678b18","url":null,"abstract":"This paper presents the design of a fire safety and security network for high-rise buildings based on wireless sensor networks. Utilizing the Zigbee system’s topology and Zigbee technology for wireless sensor network communication, the design enables intercommunication among sensor nodes, forming a multi-network system. This system facilitates the preemptive warning and dissemination of fire-related information, facilitating efficient information transmission. Simulation results affirm the practical effectiveness of this design scheme, underscoring its substantial applicability.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"26 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379258","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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