{"title":"用于探测人类危难的模糊逻辑模型","authors":"D. Ogunbiyi, Ibrahim Ogundoyin, Caleb Akanbi","doi":"10.29081/jesr.v29i3.005","DOIUrl":null,"url":null,"abstract":"Distress occurs when a person is in anxiety or fear. Existing research in distress detection arising from physical attacks focused mainly on the use of machine learning techniques. To extend research efforts, this study proposes an alternate approach using fuzzy logic. Parameters to describe physically triggered distress were identified and used as input to the designed fuzzy model. Experiments were carried out using random samples of data values to test the behavior of the model. In all cases, the model was able to show outcomes that are expected and achieved high accuracy.","PeriodicalId":15687,"journal":{"name":"Journal of Engineering Studies and Research","volume":" 14","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A FUZZY LOGIC MODEL FOR HUMAN DISTRESS DETECTION\",\"authors\":\"D. Ogunbiyi, Ibrahim Ogundoyin, Caleb Akanbi\",\"doi\":\"10.29081/jesr.v29i3.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Distress occurs when a person is in anxiety or fear. Existing research in distress detection arising from physical attacks focused mainly on the use of machine learning techniques. To extend research efforts, this study proposes an alternate approach using fuzzy logic. Parameters to describe physically triggered distress were identified and used as input to the designed fuzzy model. Experiments were carried out using random samples of data values to test the behavior of the model. In all cases, the model was able to show outcomes that are expected and achieved high accuracy.\",\"PeriodicalId\":15687,\"journal\":{\"name\":\"Journal of Engineering Studies and Research\",\"volume\":\" 14\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering Studies and Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29081/jesr.v29i3.005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering Studies and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29081/jesr.v29i3.005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distress occurs when a person is in anxiety or fear. Existing research in distress detection arising from physical attacks focused mainly on the use of machine learning techniques. To extend research efforts, this study proposes an alternate approach using fuzzy logic. Parameters to describe physically triggered distress were identified and used as input to the designed fuzzy model. Experiments were carried out using random samples of data values to test the behavior of the model. In all cases, the model was able to show outcomes that are expected and achieved high accuracy.
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