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http://dx.doi.org/10.12989/smm.2020.7.1.059

Hazard analysis and monitoring for debris flow based on intelligent fuzzy detection  

Chen, Tim (AI LAB, Faculty of Information Technology, Ton Duc Thang University)
Kuo, D. (Faculty of Science, Monash University)
Chen, J.C.Y. (Faculty of Decision Science, University of California)
Publication Information
Structural Monitoring and Maintenance / v.7, no.1, 2020 , pp. 59-67 More about this Journal
Abstract
This study aims to develop the fuzzy risk assessment model of the debris flow to verify the accuracy of risk assessment in order to help related organizations reduce losses caused by landslides. In this study, actual cases of landslides that occurred are utilized as the database. The established models help us assess the occurrence of debris flows using computed indicators, and to verify the model errors. In addition, comparisons are made between the models to determine the best one to use in practical applications. The results prove that the risk assessment model systems are quite suitable for debris flow risk assessment. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.
Keywords
landslide; natural disaster; feature based; computer vision; natural disasters detection; event warning system;
Citations & Related Records
Times Cited By KSCI : 9  (Citation Analysis)
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