A framework of Mult! Linear Regression based on Fuzzy Theory and Situation Awareness and its application to Beach Risk Assessment

Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based o...

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Veröffentlicht in:KSII transactions on Internet and information systems 2020-07, Vol.14 (7), p.3039
Hauptverfasser: Shin, Gun-Yoon, Hong, Sung-Sam, Kim, Dong-Wook, Hwang, Cheol-Hun, Han, Myung-Mook, Kim, Hwayoung, Kim, Young jae
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container_issue 7
container_start_page 3039
container_title KSII transactions on Internet and information systems
container_volume 14
creator Shin, Gun-Yoon
Hong, Sung-Sam
Kim, Dong-Wook
Hwang, Cheol-Hun
Han, Myung-Mook
Kim, Hwayoung
Kim, Young jae
description Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks. Keywords: Beach Risk Assessment, Beach Risk Factor, Situation Awareness, Fuzzy Theory, Multi Linear Regression.
doi_str_mv 10.3837/tiis.2020.07.017
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We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks. 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subjects Accidents
Regression analysis
Risk assessment
title A framework of Mult! Linear Regression based on Fuzzy Theory and Situation Awareness and its application to Beach Risk Assessment
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