发布求助
文献互助 智能选刊 最新文献

Science and Technology of Engineering, Chemistry and Environmental Protection最新文献

筛选
英文 中文
A review of brake energy recovery systems and vibration energy recovery systems in new energy vehicles 新能源汽车制动能量回收系统和振动能量回收系统综述
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/094x1d72
Hanwen Jian
{"title":"A review of brake energy recovery systems and vibration energy recovery systems in new energy vehicles","authors":"Hanwen Jian","doi":"10.61173/094x1d72","DOIUrl":"https://doi.org/10.61173/094x1d72","url":null,"abstract":"As the automotive industry faces the dual challenges of energy crisis and environmental degradation, developing new energy vehicles (NEVs) has become a focal point. This paper presents a comprehensive overview of braking and vibration energy recovery systems in NEVs. Specifically, it explores these systems’ theoretical foundations, control strategies, and current research status. The braking energy recovery system aims to enhance energy efficiency by capturing and reusing the energy generated during braking. In contrast, the vibration energy recovery system seeks to expand energy recovery channels by absorbing vehicle vibrations. While considerable research has been conducted on braking energy recovery, there is still a need for further exploration in vibration energy recovery. By optimizing these systems, we aim to contribute to the sustainable growth of the NEV industry, ultimately benefiting both the environment and energy conservation efforts.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378491","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}
引用次数: 0
An Example of Machine Learning-Based Multifactor Dynamic Quantitative Stock Picking Models 基于机器学习的多因素动态量化选股模型实例
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/7n8qt956
Haocheng Sun
{"title":"An Example of Machine Learning-Based Multifactor Dynamic Quantitative Stock Picking Models","authors":"Haocheng Sun","doi":"10.61173/7n8qt956","DOIUrl":"https://doi.org/10.61173/7n8qt956","url":null,"abstract":"This study utilizes the XGBoost algorithm in the field of machine learning to conduct quantitative stock picking research for CSI 300 stocks. The article firstly outlines the importance and practical application background of quantitative stock selection, and then discusses in depth the basic principle of XGBoost algorithm and its application method in quantitative stock selection. By collecting historical data of CSI 300 stocks and after data preprocessing, this study constructs a multi-factor stock prediction model based on XGBoost and conducts relevant backtesting. Comparative experiments show that the XGBoost algorithm exhibits good effectiveness and demonstrates the unique advantages and characteristics of its stock selection strategy. The conclusion of the study shows that the XGBoost-based stock selection strategy has potential application value in the stock market and can provide investors with accurate and efficient stock selection reference.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"317 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381395","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}
引用次数: 0
Sentiment Analysis for Film Reviews Based on Random Forest 基于随机森林的电影评论情感分析
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/5t8epb44
Dongling Zheng
{"title":"Sentiment Analysis for Film Reviews Based on Random Forest","authors":"Dongling Zheng","doi":"10.61173/5t8epb44","DOIUrl":"https://doi.org/10.61173/5t8epb44","url":null,"abstract":"Sentiment analysis of film reviews has been a popular research topic, and previous researchers have investigated it on the IMDb dataset using a variety of machine learning models, however, the classification results are not satisfactory. Therefore this study aims to construct an effective sentiment analysis model and explore whether the Random Forest algorithm can be applied to the task of sentiment analysis on the IMDb dataset. In this study, after preprocessing the data, the Random Forest model was trained using a training set and evaluated using a test set to explore the accuracy and performance of the Random Forest model in film review sentiment analysis. The study also plotted word clouds to visualize the decision-making effect of the model. The Random Forest Model achieves an impressive 86% accuracy in sentiment analysis, while the word cloud plots provide a visually appealing depiction of its classification task. This indicates that the Random Forest model performs well in the film review sentiment analysis task with high accuracy and performance.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"108 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377093","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}
引用次数: 0
A-share Trend Prediction Based on Machine Learning and Sentiment Analysis 基于机器学习和情感分析的 A 股趋势预测
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/52jy4c52
Jiaming Zhang
{"title":"A-share Trend Prediction Based on Machine Learning and Sentiment Analysis","authors":"Jiaming Zhang","doi":"10.61173/52jy4c52","DOIUrl":"https://doi.org/10.61173/52jy4c52","url":null,"abstract":"This study addresses the predictive challenges in China’s A-share market, characterized by high retail investor participation and significant policy impacts. We introduce a novel predictive model that leverages both machine learning algorithms and sentiment analysis to forecast market trends. The research utilizes comprehensive datasets, including real-time A-share market data and sentiment-derived data from stock-related news, processed via advanced machine learning techniques like Random Forest and sentiment analysis tools. Our approach innovatively combines traditional technical indicators with sentiment scores to enhance the predictive accuracy of the model. The findings suggest that integrating sentiment analysis significantly improves the model’s performance, evidenced by enhanced prediction metrics such as Mean Absolute Error (MAE) and R-squared values, which compare favorably before and after incorporating sentiment data. This study not only contributes to the existing financial prediction literature by providing a hybrid methodological approach but also offers practical implications for investors and policymakers in navigating the volatile A-share market.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"143 5‐6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381158","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}
引用次数: 0
UAV Obstacle Avoidance Technology 无人机避障技术
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/vpv1ca75
Hongyi Wang
{"title":"UAV Obstacle Avoidance Technology","authors":"Hongyi Wang","doi":"10.61173/vpv1ca75","DOIUrl":"https://doi.org/10.61173/vpv1ca75","url":null,"abstract":"This article investigates the obstacle avoidance technology of unmanned aerial vehicles (UAVs). Firstly, the background, purpose, and significance of UAV obstacle avoidance technology are introduced. Then, the domestic and foreign research status is analyzed. Next, an overall plan for UAV obstacle avoidance is proposed, including demand analysis and system design. Afterwards, the theory and specific steps of binocular stereo vision obstacle positioning are discussed in detail, including camera calibration, image rectification, and stereo matching. Furthermore, methods for estimating obstacle motion states are researched. In addition, path planning methods for obstacle avoidance are explored, with a focus on the principles, issues, and improvement methods of artificial potential field method. Finally, the main achievements of this study are summarized, and future research directions are outlined. The innovation of this article lies in the proposal of an improved artificial potential field method, and the precise obstacle positioning achieved through binocular stereo vision. Future research can further optimize the path planning methods for obstacle avoidance to enhance the effectiveness and reliability of UAV obstacle avoidance.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"102 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377997","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}
引用次数: 0
A literature review of pneumonia detection algorithms based on deep learning and chest X-ray imaging 基于深度学习和胸部 X 光成像的肺炎检测算法文献综述
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/wpf17b07
Chenyu Wang
{"title":"A literature review of pneumonia detection algorithms based on deep learning and chest X-ray imaging","authors":"Chenyu Wang","doi":"10.61173/wpf17b07","DOIUrl":"https://doi.org/10.61173/wpf17b07","url":null,"abstract":"Pneumonia is a serious disease that poses a threat to people’s health of all ages. It could happen when people are infected by viruses, fungi, bacteria etc. Typically, Chest X-rays are the first and foremost imaging approach to implement pneumonia detection. This paper introduces the latest research achievements to help those who are new in this field to have basic intuition about AI in pneumonia detection., including Vision Transformers on chest X-ray, a novel model based on RetinaNet, CP_DeepNet, and a novel Efficient NetV2L model. The last part gives some suggestions about the future study of pneumonia detection using Deep learning.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"30 51","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378711","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}
引用次数: 0
Research on UAV-assisted Vehicle networking task unloading strategy based on multi-agent reinforcement learning 基于多代理强化学习的无人机辅助车联网任务卸载策略研究
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/ceadt415
Fanjin Zeng
{"title":"Research on UAV-assisted Vehicle networking task unloading strategy based on multi-agent reinforcement learning","authors":"Fanjin Zeng","doi":"10.61173/ceadt415","DOIUrl":"https://doi.org/10.61173/ceadt415","url":null,"abstract":"With the development of technology, in order to improve the user’s driving experience and driving safety, there are more and more vehicle tasks with high delay requirements.  Therefore, lots of researchers have paid attention to task offloading scheduling.However, as vehicle tasks become increasingly complex, a single task may consist of multiple subtasks with dependencies between them.The complex data dependencies within them make it more and more difficult to design appropriate task offloading strategies. Considering that this problem is closely related to the scenarios and requirements in the real world, this study focuses on the design of task offloading decisions in the scenario of UAV-assisted vehicle network, in which MEC servers are installed in the macro base station and UAV to provide computing resources for vehicles. We designed a task offloading strategy based on MATD3 algorithm to deal with this problem. Following simulation trials, it is evident that our approach offers notable benefits in terms of both delay and energy usage.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"30 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378579","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}
引用次数: 0
Research on the Influencing Factors of Housing Satisfaction 住房满意度影响因素研究
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/p3g1ht41
Maimu Yang
{"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}
引用次数: 0
Exploring Multiple Regression Models: Key Concepts and Applications 探索多元回归模型：关键概念与应用
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/yjpt3s59
Yanbo Ruan
{"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}
引用次数: 0
Research on Urban Land Use based on Remote Sensing Technology 基于遥感技术的城市土地利用研究
Science and Technology of Engineering, Chemistry and Environmental Protection Pub Date : 2024-06-06 DOI: 10.61173/9smr3z05
Xiaochun Xu
{"title":"Research on Urban Land Use based on Remote Sensing Technology","authors":"Xiaochun Xu","doi":"10.61173/9smr3z05","DOIUrl":"https://doi.org/10.61173/9smr3z05","url":null,"abstract":"The advancement of urbanization has brought urban land use change into the spotlight of research. Remote sensing technology, as the primary means of capturing this change, provides valuable data for research. The main research object of this paper is the four classification methods of land use in cities based on remote sensing technology, and it outlines the main roles and applications of these four classification methods. This paper concludes that the visual interpretation method is less efficient but widely used. In addition, the accuracy of supervised classification and deep learning methods for classification is low. Unsupervised classification is simple, but the results differ greatly from reality. The above commonly used land classification methods have their advantages and disadvantages, and their combined use ensures that remote sensing technology provides real-time, effective, and comprehensive land use information for urban planning and management. Finally, this paper looks forward to the combination of remote sensing technology and modern technology, such as artificial intelligence. The integrated technology can provide more accurate and efficient technical support for future urban development.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381565","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}
引用次数: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信
小红书