With the requirements of a high-quality development strategy, new urbanization also takes high quality as the development goal. This paper utilizes Henan Province as the spatial research carrier to screen and construct a model for urbanization high-quality development and ecological and culturally coordinated development. Comprehensive use of ArcGIS spatial analysis, coupled coordination degree model, synchronicity model and Markov chain and other methods and other methods of the main system, to analyze the regional differences in the level of high-quality and coordinated development of urbanization in Henan Province and the spatial evolution process. It also explores the evolutionary characteristics and functional interaction between urbanization and ecological culture in Henan from the perspective of high-quality development. The results show that the level of urbanization in Henan Province under the integration of ecological culture has been steadily increasing, but there is a large gap between the urbanization levels of various regions. Significant differences exist between the high-quality synergistic development of urbanization in Zhengzhou at the highest level of 0.7782 in the 2022 time period and the low level of only 0.33. This study can provide corresponding policy recommendations for the high-quality development of urbanization in Henan Province, as well as a reference for other provinces with similar urbanization processes as Henan Province.
{"title":"Research on the Path of Integrating Ecological Culture into the High-Quality Development of Henan Urbanization in the Era of Big Data","authors":"Xingwei Wang","doi":"10.2478/amns-2024-0133","DOIUrl":"https://doi.org/10.2478/amns-2024-0133","url":null,"abstract":"\u0000 With the requirements of a high-quality development strategy, new urbanization also takes high quality as the development goal. This paper utilizes Henan Province as the spatial research carrier to screen and construct a model for urbanization high-quality development and ecological and culturally coordinated development. Comprehensive use of ArcGIS spatial analysis, coupled coordination degree model, synchronicity model and Markov chain and other methods and other methods of the main system, to analyze the regional differences in the level of high-quality and coordinated development of urbanization in Henan Province and the spatial evolution process. It also explores the evolutionary characteristics and functional interaction between urbanization and ecological culture in Henan from the perspective of high-quality development. The results show that the level of urbanization in Henan Province under the integration of ecological culture has been steadily increasing, but there is a large gap between the urbanization levels of various regions. Significant differences exist between the high-quality synergistic development of urbanization in Zhengzhou at the highest level of 0.7782 in the 2022 time period and the low level of only 0.33. This study can provide corresponding policy recommendations for the high-quality development of urbanization in Henan Province, as well as a reference for other provinces with similar urbanization processes as Henan Province.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140517993","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 an emerging driving force to promote rural revitalization, sports tourism provides tourists with rich experiences and effectively promotes the development of local sports industry and economy. In this study, an integrated transfer learning model is constructed to assess the development level of rural revitalization by combining a constrained LightGBM-based learner, a Gaussian distribution and an optimized sampling function. Applying this model, this paper calculates the integrated development index of rural revitalization for 21 provinces, municipalities and autonomous regions in China between 2019 and 2023. Particularly for Tianjin, the study finds that its comprehensive development index for rural revitalization is relatively low, only 0.244 in 2023. Analyzing the cases of six typical villages in Tianjin, the study finds that sports tourism significantly impacts rural revitalization. During the five years, the average annual growth of tourist arrivals amounted to 125,400 visitors, and the average tourism revenue in 2023 reached 9.686 billion yuan. Meanwhile, these villages had an average of 3.79 points in the development level of living affluence, which is a high level. The study provides empirical support for sports tourism to help rural revitalization. It provides practical references for the future development direction and planning of rural sports tourism, emphasizing the critical role of sports tourism in promoting the comprehensive development of villages.
{"title":"A Logical Rationale for Sports Tourism to Help Rural Revitalization under Integrated Transfer Learning Strategy","authors":"Chengwei Liu, Ning Yang","doi":"10.2478/amns-2024-0497","DOIUrl":"https://doi.org/10.2478/amns-2024-0497","url":null,"abstract":"\u0000 As an emerging driving force to promote rural revitalization, sports tourism provides tourists with rich experiences and effectively promotes the development of local sports industry and economy. In this study, an integrated transfer learning model is constructed to assess the development level of rural revitalization by combining a constrained LightGBM-based learner, a Gaussian distribution and an optimized sampling function. Applying this model, this paper calculates the integrated development index of rural revitalization for 21 provinces, municipalities and autonomous regions in China between 2019 and 2023. Particularly for Tianjin, the study finds that its comprehensive development index for rural revitalization is relatively low, only 0.244 in 2023. Analyzing the cases of six typical villages in Tianjin, the study finds that sports tourism significantly impacts rural revitalization. During the five years, the average annual growth of tourist arrivals amounted to 125,400 visitors, and the average tourism revenue in 2023 reached 9.686 billion yuan. Meanwhile, these villages had an average of 3.79 points in the development level of living affluence, which is a high level. The study provides empirical support for sports tourism to help rural revitalization. It provides practical references for the future development direction and planning of rural sports tourism, emphasizing the critical role of sports tourism in promoting the comprehensive development of villages.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140519177","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}
New energy vehicles are vital in promoting environmental protection and technological innovation. Fault detection still faces challenges during its operation, and efficient and accurate methods for fault diagnosis are urgently needed. This paper proposes a fault detection and analysis model based on a decision tree algorithm for the fault detection problem of new energy vehicles. The dataset applicable to the model is prepared by preprocessing in-vehicle network data, including data cleaning, integration, and other steps. Fault prediction can be realized after using C4.5 algorithms to construct a decision tree. With a precision of 82.26% on the test set, this model is highly accurate in fault detection, which is 1.23 percentage points higher than the traditional decision tree algorithm. The model’s effectiveness and efficiency in handling large-scale data were demonstrated by its training and testing on training sets of different sizes. Using the traditional algorithm, a training set of 80,000 data was used to reduce the model’s running time from 274,432 seconds to 249,269 seconds. This study provides a practical methodology for fault diagnosis of new energy vehicles, improving fault detection accuracy while optimizing computational efficiency. Real-time monitoring and timely maintenance of new energy vehicles require this.
{"title":"Fault Detection and Failure Rate Analysis of New Energy Vehicles Based on Decision Tree Algorithm","authors":"Ping Tan, Lanlan Gong","doi":"10.2478/amns-2024-0803","DOIUrl":"https://doi.org/10.2478/amns-2024-0803","url":null,"abstract":"\u0000 New energy vehicles are vital in promoting environmental protection and technological innovation. Fault detection still faces challenges during its operation, and efficient and accurate methods for fault diagnosis are urgently needed. This paper proposes a fault detection and analysis model based on a decision tree algorithm for the fault detection problem of new energy vehicles. The dataset applicable to the model is prepared by preprocessing in-vehicle network data, including data cleaning, integration, and other steps. Fault prediction can be realized after using C4.5 algorithms to construct a decision tree. With a precision of 82.26% on the test set, this model is highly accurate in fault detection, which is 1.23 percentage points higher than the traditional decision tree algorithm. The model’s effectiveness and efficiency in handling large-scale data were demonstrated by its training and testing on training sets of different sizes. Using the traditional algorithm, a training set of 80,000 data was used to reduce the model’s running time from 274,432 seconds to 249,269 seconds. This study provides a practical methodology for fault diagnosis of new energy vehicles, improving fault detection accuracy while optimizing computational efficiency. Real-time monitoring and timely maintenance of new energy vehicles require this.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140517380","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 an effective economic decision-making tool in enterprise economic management, Marginal Analysis is crucial to reflect the small change relationship between costs and benefits. This paper aims to develop a multi-objective marginal analysis optimization algorithm (MMAOA) that utilizes marginal analysis to optimize the enterprise economic management model and risk control. This algorithm's improvement of the population initialization method and constraint handling enhances the quality of understanding and search efficiency. In this study, an improved population initialization method is designed to ensure that the population is within the upper and lower limits of the output power. Then the constraints are reasonably handled by the penalty function method and the correction method to enhance the feasibility and robustness of the algorithm. Guided by the concept of Pareto optimality, MMAOA is successfully applied to multi-objective optimization problems, and the algorithm can efficiently generate a set of Pareto optimal solutions under the consideration of equilibrium constraints and inequality constraints, in which the objective function values of certain optimization instances are improved by more than 10%. Following marginal analysis, this study presents the disparity in ROI between the East and West and the three stages of agricultural economic efficiency. This article provides a new optimization tool for enterprise financial management and a quantitative analysis method for risk assessment.
{"title":"Optimization of Enterprise Economic Management Model and Risk Control Based on Marginal Analysis Approach","authors":"Xiaoyun Wu","doi":"10.2478/amns-2024-0809","DOIUrl":"https://doi.org/10.2478/amns-2024-0809","url":null,"abstract":"\u0000 As an effective economic decision-making tool in enterprise economic management, Marginal Analysis is crucial to reflect the small change relationship between costs and benefits. This paper aims to develop a multi-objective marginal analysis optimization algorithm (MMAOA) that utilizes marginal analysis to optimize the enterprise economic management model and risk control. This algorithm's improvement of the population initialization method and constraint handling enhances the quality of understanding and search efficiency. In this study, an improved population initialization method is designed to ensure that the population is within the upper and lower limits of the output power. Then the constraints are reasonably handled by the penalty function method and the correction method to enhance the feasibility and robustness of the algorithm. Guided by the concept of Pareto optimality, MMAOA is successfully applied to multi-objective optimization problems, and the algorithm can efficiently generate a set of Pareto optimal solutions under the consideration of equilibrium constraints and inequality constraints, in which the objective function values of certain optimization instances are improved by more than 10%. Following marginal analysis, this study presents the disparity in ROI between the East and West and the three stages of agricultural economic efficiency. This article provides a new optimization tool for enterprise financial management and a quantitative analysis method for risk assessment.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140526809","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 an era where science, technology, and innovation are key drivers of urban transformation, this research addresses the critical influences of policy and practice on urban planning and land utilization, proposing efficacious planning strategies to navigate emerging challenges. The study offers a comprehensive examination of urban development trends by integrating methods such as fuzzy set urban planning models, multi-objective planning, fuzzy regression, and GIS-based land use analysis. Specifically, our analysis of Shenzhen’s expansion and agricultural land growth from 1998 to 2023 demonstrates the significant impacts of technological innovation on urban landscapes, notably in expanding built-up regions by 90.21 square kilometers and augmenting greenfield farmland by 17.83%, thereby markedly enhancing land designated for ecological purposes. These findings affirm the vital role of innovation in advancing environmental sustainability and sustainable urban planning practices.
{"title":"Science, technology and innovation driving urban land use and urban planning development: policy and practice","authors":"Jianan Min, Zicong Liu","doi":"10.2478/amns-2024-0703","DOIUrl":"https://doi.org/10.2478/amns-2024-0703","url":null,"abstract":"\u0000 In an era where science, technology, and innovation are key drivers of urban transformation, this research addresses the critical influences of policy and practice on urban planning and land utilization, proposing efficacious planning strategies to navigate emerging challenges. The study offers a comprehensive examination of urban development trends by integrating methods such as fuzzy set urban planning models, multi-objective planning, fuzzy regression, and GIS-based land use analysis. Specifically, our analysis of Shenzhen’s expansion and agricultural land growth from 1998 to 2023 demonstrates the significant impacts of technological innovation on urban landscapes, notably in expanding built-up regions by 90.21 square kilometers and augmenting greenfield farmland by 17.83%, thereby markedly enhancing land designated for ecological purposes. These findings affirm the vital role of innovation in advancing environmental sustainability and sustainable urban planning practices.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527067","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 far as the current situation of children’s English picture book translation and reading teaching is concerned, there exists the phenomenon that teachers pay little attention to translation and reading teaching, and the teaching effectiveness is low. This paper evaluates the translation and teaching of English picture books to children using the theory of multiple intelligences. The problem of data input and output is solved through the decision-making unit (DMU) as well as the C 2 R model composed of the DEA model. Based on the fuzzy comprehensive evaluation method and the target classification method to evaluate the students’ English learning quality and design the evaluation module, we construct the children’s picture book English teaching model under the combination of the DEA model and the multiple intelligences theory, and at the same time, we take the eight domains of the multiple intelligences theory as the evaluation indexes, combine the fuzzy comprehensive evaluation and the principle of the target classification method to evaluate the student’s learning quality of the English picture book translation and reading to analyze The status quo of children’s English picture book teaching under the theory of multiple intelligences as well as the teaching results, comparing the results of the students in the two classes and analyzing the data results statistically. Students are most interested in reading children’s English picture books when they are between 0 and 2.4. The experimental class has a higher translation skill score than the control class, with an increase of 2.79875, 2.225, and 1.975, and the translation part of the improvement is more effective.
就目前儿童英语绘本翻译与阅读教学的现状而言，存在着教师对翻译与阅读教学重视程度不高、教学效果不明显的现象。本文运用多元智能理论对儿童英语绘本翻译与阅读教学进行了评价。通过决策单元（DMU）以及由 DEA 模型组成的 C 2 R 模型，解决了数据输入和输出的问题。基于模糊综合评价法和目标分类法对学生英语学习质量进行评价并设计评价模块，构建DEA模型与多元智能理论相结合的儿童绘本英语教学模式，同时以多元智能理论的八个领域作为评价指标、结合模糊综合评价法和目标分类法的原理，对学生的英语绘本翻译阅读学习质量进行评价，分析多元智能理论下儿童英语绘本教学的现状以及教学效果，比较两个班级学生的成绩，对数据结果进行统计分析。0-2.4岁的学生对阅读儿童英语绘本最感兴趣。实验班的翻译能力得分比对照班高，分别提高了2.79875、2.225、1.975，翻译部分的提高效果更好。
{"title":"An Exploration of Children’s English Picture Book Translation and Reading Teaching Based on Multiple Intelligences Theory","authors":"Lihua He, Yi Li","doi":"10.2478/amns-2024-0089","DOIUrl":"https://doi.org/10.2478/amns-2024-0089","url":null,"abstract":"\u0000 As far as the current situation of children’s English picture book translation and reading teaching is concerned, there exists the phenomenon that teachers pay little attention to translation and reading teaching, and the teaching effectiveness is low. This paper evaluates the translation and teaching of English picture books to children using the theory of multiple intelligences. The problem of data input and output is solved through the decision-making unit (DMU) as well as the C\u0000 2\u0000 R model composed of the DEA model. Based on the fuzzy comprehensive evaluation method and the target classification method to evaluate the students’ English learning quality and design the evaluation module, we construct the children’s picture book English teaching model under the combination of the DEA model and the multiple intelligences theory, and at the same time, we take the eight domains of the multiple intelligences theory as the evaluation indexes, combine the fuzzy comprehensive evaluation and the principle of the target classification method to evaluate the student’s learning quality of the English picture book translation and reading to analyze The status quo of children’s English picture book teaching under the theory of multiple intelligences as well as the teaching results, comparing the results of the students in the two classes and analyzing the data results statistically. Students are most interested in reading children’s English picture books when they are between 0 and 2.4. The experimental class has a higher translation skill score than the control class, with an increase of 2.79875, 2.225, and 1.975, and the translation part of the improvement is more effective.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140517183","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 digital economy has become an important driving force for green energy consumption, and its impact has covered rural areas. This paper establishes a comprehensive evaluation model of green energy consumption based on group principal component analysis, and at the same time establishes evaluation indicators of the green energy consumption level of rural residents to explore the impact of the development of the digital economy on green energy consumption. Based on the comprehensive evaluation model and evaluation indexes, the green energy consumption level of rural residents in the “2+26” cities and the three major economic zones is analyzed. The rural areas with higher green energy consumption levels by 2022 include Tangshan, Jining, and Kaifeng, with 0.794, 0.788, and 0.852, respectively. The willingness of rural residents in the three major economic zones to consume green energy is in line with the trend of the degree of development of the digital economy, in which the willingness to consume green energy is highest among rural residents under the age of 20 in the eastern region, with an average of 4.81. At the same time, the development of the digital economy has a direct effect on the level of consumption of green energy. The regression coefficient of the direct effect on the level of green energy consumption is 0.289. Overall, the development of the digital economy has a greater promotion effect on the level and willingness of rural residents to consume green energy.
{"title":"Exploring the Impact of Digital Economic Development on Green Energy Consumption of Rural Residents Using Principal Component Analysis Methods","authors":"Jing An","doi":"10.2478/amns-2024-0187","DOIUrl":"https://doi.org/10.2478/amns-2024-0187","url":null,"abstract":"\u0000 The digital economy has become an important driving force for green energy consumption, and its impact has covered rural areas. This paper establishes a comprehensive evaluation model of green energy consumption based on group principal component analysis, and at the same time establishes evaluation indicators of the green energy consumption level of rural residents to explore the impact of the development of the digital economy on green energy consumption. Based on the comprehensive evaluation model and evaluation indexes, the green energy consumption level of rural residents in the “2+26” cities and the three major economic zones is analyzed. The rural areas with higher green energy consumption levels by 2022 include Tangshan, Jining, and Kaifeng, with 0.794, 0.788, and 0.852, respectively. The willingness of rural residents in the three major economic zones to consume green energy is in line with the trend of the degree of development of the digital economy, in which the willingness to consume green energy is highest among rural residents under the age of 20 in the eastern region, with an average of 4.81. At the same time, the development of the digital economy has a direct effect on the level of consumption of green energy. The regression coefficient of the direct effect on the level of green energy consumption is 0.289. Overall, the development of the digital economy has a greater promotion effect on the level and willingness of rural residents to consume green energy.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140523310","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 evolving field of educational technology, knowledge mapping has emerged as a pivotal tool for university English education. This study examines its role in building a theoretical resource base to enhance the efficiency of organizing, accessing, and utilizing teaching materials. This research constructs a knowledge graph for English teaching resources by employing a seven-step process to create a domain ontology and an enhanced TF-IDF algorithm for keyword extraction. Results show the knowledge graph significantly boosts information retrieval accuracy and user satisfaction. The experimental group reported a 25% increase in learning efficiency, a 30% enhancement in the quality of learning outcomes, and a 12.63% rise in average grades, outperforming the control group. The findings suggest knowledge mapping substantially benefits the development of a theoretical resource base for university English teaching, improving teaching and learning quality.
{"title":"Knowledge Mapping Applied to the Construction of a Theoretical Resource Base for Teaching English at the University Level","authors":"Xia Xie","doi":"10.2478/amns-2024-0798","DOIUrl":"https://doi.org/10.2478/amns-2024-0798","url":null,"abstract":"\u0000 In the evolving field of educational technology, knowledge mapping has emerged as a pivotal tool for university English education. This study examines its role in building a theoretical resource base to enhance the efficiency of organizing, accessing, and utilizing teaching materials. This research constructs a knowledge graph for English teaching resources by employing a seven-step process to create a domain ontology and an enhanced TF-IDF algorithm for keyword extraction. Results show the knowledge graph significantly boosts information retrieval accuracy and user satisfaction. The experimental group reported a 25% increase in learning efficiency, a 30% enhancement in the quality of learning outcomes, and a 12.63% rise in average grades, outperforming the control group. The findings suggest knowledge mapping substantially benefits the development of a theoretical resource base for university English teaching, improving teaching and learning quality.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140519239","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}
Ruixin Zhao, SaiHong Tang, E. Supeni, S. Rahim, Luxin Fan
At the current stage, the rapid Development of autonomous driving has made object detection in traffic scenarios a vital research task. Object detection is the most critical and challenging task in computer vision. Deep learning, with its powerful feature extraction capabilities, has found widespread applications in safety, military, and medical fields, and in recent years has expanded into the field of transportation, achieving significant breakthroughs. This survey is based on the theory of deep learning. It systematically summarizes the Development and current research status of object detection algorithms, and compare the characteristics, advantages and disadvantages of the two types of algorithms. With a focus on traffic signs, vehicle detection, and pedestrian detection, it summarizes the applications and research status of object detection in traffic scenarios, highlighting the strengths, limitations, and applicable scenarios of various methods. It introduces techniques for optimizing object detection algorithms, summarizes commonly used object detection datasets and traffic scene datasets, along with evaluation criteria, and performs comparative analysis of the performance of deep learning algorithms. Finally, it concludes the development trends of object detection algorithms in traffic scenarios, providing research directions for intelligent transportation and autonomous driving.
{"title":"A Review of Object Detection in Traffic Scenes Based on Deep Learning","authors":"Ruixin Zhao, SaiHong Tang, E. Supeni, S. Rahim, Luxin Fan","doi":"10.2478/amns-2024-0322","DOIUrl":"https://doi.org/10.2478/amns-2024-0322","url":null,"abstract":"\u0000 At the current stage, the rapid Development of autonomous driving has made object detection in traffic scenarios a vital research task. Object detection is the most critical and challenging task in computer vision. Deep learning, with its powerful feature extraction capabilities, has found widespread applications in safety, military, and medical fields, and in recent years has expanded into the field of transportation, achieving significant breakthroughs. This survey is based on the theory of deep learning. It systematically summarizes the Development and current research status of object detection algorithms, and compare the characteristics, advantages and disadvantages of the two types of algorithms. With a focus on traffic signs, vehicle detection, and pedestrian detection, it summarizes the applications and research status of object detection in traffic scenarios, highlighting the strengths, limitations, and applicable scenarios of various methods. It introduces techniques for optimizing object detection algorithms, summarizes commonly used object detection datasets and traffic scene datasets, along with evaluation criteria, and performs comparative analysis of the performance of deep learning algorithms. Finally, it concludes the development trends of object detection algorithms in traffic scenarios, providing research directions for intelligent transportation and autonomous driving.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140517488","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}
Good sports interest helps college students to actively participate in physical exercise, excellently complete sports tasks, form good sports habits and have a strong body. Given this, this paper establishes an innovative model of college physical education based on the 4R Theory, fully integrates physical education services with classroom teaching, and designs teaching experiments related to physical education services and sports education in colleges and universities. The subjects were Chengdu University of Technology students. The cluster analysis algorithm was used to cluster students’ sports interests, and the parameter estimation of the multiple linear regression model was carried out by the least squares method to deeply analyze the relevant factors affecting students’ sports interests in colleges and universities. The study found that: students’ sports interest clustering is divided into five categories, the number of students in cluster 1 sports awareness reached 542, and students’ sports interest increased by 0.627 percentage points for every 1 percentage point increase in sports skills, and students’ sports participation interest in the experimental class increased by 46.79% compared to that of the control class after the experiment. Adopting diversified physical education teaching methods and contents can effectively enhance college students’ interest in sports, thus providing guarantee for improving students’ physical fitness.
{"title":"Exploring the development of college students’ sports interests in physical education based on cluster analysis","authors":"Yegang Zheng","doi":"10.2478/amns-2024-0532","DOIUrl":"https://doi.org/10.2478/amns-2024-0532","url":null,"abstract":"\u0000 Good sports interest helps college students to actively participate in physical exercise, excellently complete sports tasks, form good sports habits and have a strong body. Given this, this paper establishes an innovative model of college physical education based on the 4R Theory, fully integrates physical education services with classroom teaching, and designs teaching experiments related to physical education services and sports education in colleges and universities. The subjects were Chengdu University of Technology students. The cluster analysis algorithm was used to cluster students’ sports interests, and the parameter estimation of the multiple linear regression model was carried out by the least squares method to deeply analyze the relevant factors affecting students’ sports interests in colleges and universities. The study found that: students’ sports interest clustering is divided into five categories, the number of students in cluster 1 sports awareness reached 542, and students’ sports interest increased by 0.627 percentage points for every 1 percentage point increase in sports skills, and students’ sports participation interest in the experimental class increased by 46.79% compared to that of the control class after the experiment. Adopting diversified physical education teaching methods and contents can effectively enhance college students’ interest in sports, thus providing guarantee for improving students’ physical fitness.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140522231","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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