English  |  正體中文  |  简体中文  |  Items with full text/Total items : 64178/96951 (66%)
Visitors : 11066143      Online Users : 23555
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/121783


    Title: New debris flow critical rainfall line setting via cluster analysis and support vector machine after the Chi-Chi huge earthquake
    Authors: Tsai, Yuan-Fang;Chan, Chun-Hsiang;Lin, Keng-Han;Su, Wen-Ray;Chen, Jinn-Chyi
    Keywords: cluster analysis;support vector machine;debris flow;critical rainfall line;earthquake
    Date: 2017-07-29
    Issue Date: 2021-12-20 12:12:19 (UTC+8)
    Abstract: The Chi-Chi huge earthquake occurred in Taiwan in 1999 and it caused landslides and debris flows, which brought about considerable loss of life and property. To help prevent damage by debris flows, it is necessary to establish a new critical rainfall line of debris flow. Following the Chi-Chi huge earthquake, the rainfall threshold of debris flow streams in Taiwan was ostensibly reduced. To comprehend these changes, this study used a four-year (1999-2003) dataset of 79 debris flow events, and it adopted the family competition genetic algorithm as a clustering method to merge rainfall data of streams based on similar characteristics. In addition, 8 predisposing features for debris flows were used to cluster 377 streams with similar predisposing features into 7 groups, and this study used a family competition genetic algorithm. Then, this study apply the support vector machine (SVM) for establishing new critical rainfall lines. Experimental results confirmed that the FCGA and the SVM method performed well in setting a new critical rainfall line.
    Relation: 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, p.1005-1010
    DOI: 10.1109/FSKD.2017.8392859
    Appears in Collections:[Department of Artificial Intelligence] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML129View/Open
    New debris flow critical rainfall line setting via cluster analysis and support vector machine after the Chi-Chi huge earthquake.pdf660KbAdobe PDF1View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback