Chandrakirishnan Balakrishnan Sivaparthipan, Priyan Malarvizhi Kumar, Thota Chandu, BalaAnand Muthu, Mohammed Hasan Ali, Boris Tomaš
{"title":"基于本体的推测感模型对倦怠人群大脑图像的分类分析","authors":"Chandrakirishnan Balakrishnan Sivaparthipan, Priyan Malarvizhi Kumar, Thota Chandu, BalaAnand Muthu, Mohammed Hasan Ali, Boris Tomaš","doi":"10.1111/coin.12595","DOIUrl":null,"url":null,"abstract":"<p>Burnout is a state of exhaustion that results from prolonged, excessive workplace stress. This can be examined with the biological explications of burnout and physical consequences and classified against prolonged vigorous activities. The research aims to classify burnout people's brain images against prolonged emotional activities using ontology analysis of treatment and prevention and intermediate layers formation based on a speculative sense model. In this segment, the Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model is employed for burnout people's classification analysis. The methodology is performed in the platform of ontology creation and performs the classification analysis. The calculation analysis found the result, and the brain images were classified. The classification analysis of burnout people's brain images, separation of prolonged vigorous activities, and the ontology creation for treatment and prevention against burnout people's brain images were obtained. The analysis received the result, and the results of the precision, recall, storage, computation time, specificity, and classification of burnout people's brain images were obtained. Furthermore, all these Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model had the prediction sensitivity (SN) over 50% and specificity (SP) over 90%. The Classification of Burnout People's Brain performance comparison shows that the proposed system is much more successful than existing methods, especially on a scoring accuracy of 98%.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification analysis of burnout people's brain images using ontology-based speculative sense model\",\"authors\":\"Chandrakirishnan Balakrishnan Sivaparthipan, Priyan Malarvizhi Kumar, Thota Chandu, BalaAnand Muthu, Mohammed Hasan Ali, Boris Tomaš\",\"doi\":\"10.1111/coin.12595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Burnout is a state of exhaustion that results from prolonged, excessive workplace stress. This can be examined with the biological explications of burnout and physical consequences and classified against prolonged vigorous activities. The research aims to classify burnout people's brain images against prolonged emotional activities using ontology analysis of treatment and prevention and intermediate layers formation based on a speculative sense model. In this segment, the Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model is employed for burnout people's classification analysis. The methodology is performed in the platform of ontology creation and performs the classification analysis. The calculation analysis found the result, and the brain images were classified. The classification analysis of burnout people's brain images, separation of prolonged vigorous activities, and the ontology creation for treatment and prevention against burnout people's brain images were obtained. The analysis received the result, and the results of the precision, recall, storage, computation time, specificity, and classification of burnout people's brain images were obtained. Furthermore, all these Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model had the prediction sensitivity (SN) over 50% and specificity (SP) over 90%. The Classification of Burnout People's Brain performance comparison shows that the proposed system is much more successful than existing methods, especially on a scoring accuracy of 98%.</p>\",\"PeriodicalId\":55228,\"journal\":{\"name\":\"Computational Intelligence\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2023-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Intelligence\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/coin.12595\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Intelligence","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/coin.12595","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Classification analysis of burnout people's brain images using ontology-based speculative sense model
Burnout is a state of exhaustion that results from prolonged, excessive workplace stress. This can be examined with the biological explications of burnout and physical consequences and classified against prolonged vigorous activities. The research aims to classify burnout people's brain images against prolonged emotional activities using ontology analysis of treatment and prevention and intermediate layers formation based on a speculative sense model. In this segment, the Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model is employed for burnout people's classification analysis. The methodology is performed in the platform of ontology creation and performs the classification analysis. The calculation analysis found the result, and the brain images were classified. The classification analysis of burnout people's brain images, separation of prolonged vigorous activities, and the ontology creation for treatment and prevention against burnout people's brain images were obtained. The analysis received the result, and the results of the precision, recall, storage, computation time, specificity, and classification of burnout people's brain images were obtained. Furthermore, all these Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model had the prediction sensitivity (SN) over 50% and specificity (SP) over 90%. The Classification of Burnout People's Brain performance comparison shows that the proposed system is much more successful than existing methods, especially on a scoring accuracy of 98%.
期刊介绍:
This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research.