{"title":"人工智能和机器学习在交通运输中的作用和关键应用","authors":"Memoona Shaheen, M. Arshad, Owais Iqbal","doi":"10.47672/ejt.632","DOIUrl":null,"url":null,"abstract":"Purpose: The main target of this paper was to examine the significance of Artificial Intelligence and Machine Learning and their effect on the transportation business. \nMethodology: This hypothesis was a survey of the significant machine learning calculations and their applications in the field of big data. This paper try to attempt to exhibit the need to remove significant data from the huge measure of enormous information as traffic data available in this day and age and recorded diverse machine learning strategies that can be utilized to separate this information needed to encourage better dynamic for transportation applications. \nFindings: This paper present an investigation of the different Artificial Intelligence (AI) methods that have been actualized to improve Intelligent Transportation Systems (ITS). Specifically, this paper assembled them into three main territories relying upon the main field where they were applied: Vehicle control, Traffic control and prediction, and Road security and accident prediction. The aftereffects of this examination uncover that the mix of various AI methodologies is by all accounts promising, particularly to oversee and investigate the huge measure of data created in transportation","PeriodicalId":55090,"journal":{"name":"Glass Technology-European Journal of Glass Science and Technology Part a","volume":"7 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Role and Key Applications of Artificial Intelligence & Machine Learning in Transportation\",\"authors\":\"Memoona Shaheen, M. Arshad, Owais Iqbal\",\"doi\":\"10.47672/ejt.632\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose: The main target of this paper was to examine the significance of Artificial Intelligence and Machine Learning and their effect on the transportation business. \\nMethodology: This hypothesis was a survey of the significant machine learning calculations and their applications in the field of big data. This paper try to attempt to exhibit the need to remove significant data from the huge measure of enormous information as traffic data available in this day and age and recorded diverse machine learning strategies that can be utilized to separate this information needed to encourage better dynamic for transportation applications. \\nFindings: This paper present an investigation of the different Artificial Intelligence (AI) methods that have been actualized to improve Intelligent Transportation Systems (ITS). Specifically, this paper assembled them into three main territories relying upon the main field where they were applied: Vehicle control, Traffic control and prediction, and Road security and accident prediction. The aftereffects of this examination uncover that the mix of various AI methodologies is by all accounts promising, particularly to oversee and investigate the huge measure of data created in transportation\",\"PeriodicalId\":55090,\"journal\":{\"name\":\"Glass Technology-European Journal of Glass Science and Technology Part a\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2020-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Glass Technology-European Journal of Glass Science and Technology Part a\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.47672/ejt.632\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATERIALS SCIENCE, CERAMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Glass Technology-European Journal of Glass Science and Technology Part a","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.47672/ejt.632","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATERIALS SCIENCE, CERAMICS","Score":null,"Total":0}
Role and Key Applications of Artificial Intelligence & Machine Learning in Transportation
Purpose: The main target of this paper was to examine the significance of Artificial Intelligence and Machine Learning and their effect on the transportation business.
Methodology: This hypothesis was a survey of the significant machine learning calculations and their applications in the field of big data. This paper try to attempt to exhibit the need to remove significant data from the huge measure of enormous information as traffic data available in this day and age and recorded diverse machine learning strategies that can be utilized to separate this information needed to encourage better dynamic for transportation applications.
Findings: This paper present an investigation of the different Artificial Intelligence (AI) methods that have been actualized to improve Intelligent Transportation Systems (ITS). Specifically, this paper assembled them into three main territories relying upon the main field where they were applied: Vehicle control, Traffic control and prediction, and Road security and accident prediction. The aftereffects of this examination uncover that the mix of various AI methodologies is by all accounts promising, particularly to oversee and investigate the huge measure of data created in transportation
期刊介绍:
The Journal of the Society of Glass Technology was published between 1917 and 1959. There were four or six issues per year depending on economic circumstances of the Society and the country. Each issue contains Proceedings, Transactions, Abstracts, News and Reviews, and Advertisements, all thesesections were numbered separately. The bound volumes collected these pages into separate sections, dropping the adverts. There is a list of Council members and Officers of the Society and earlier volumes also had lists of personal and company members.
JSGT was divided into Part A Glass Technology and Part B Physics and Chemistry of Glasses in 1960.