A framework of Multi 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, 14(7), , pp.3039-3056
Hauptverfasser: 신건윤, Sung-Sam Hong, Dong-Wook Kim, Cheol-Hun Hwang, Myung-Mook Han, Hwayoung Kim, Young jae Kim
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Sprache:eng
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Zusammenfassung: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. KCI Citation Count: 0
ISSN:1976-7277
1976-7277
DOI:10.3837/tiis.2020.07.017