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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/50077


    Title: Exploring the Deterioration Factors of RC Bridge Decks: A Rough Set Approach
    Authors: Huang,RY;Mao,IS;Lee,HK
    Contributors: 營建管理研究所
    Keywords: GRADIENT LEARNING ALGORITHM;SHARED-MEMORY MACHINES;NEURAL-NETWORKS;IDENTIFICATION;VIBRATION;MODEL;ACQUISITION;HEURISTICS;MANAGEMENT;DIAGNOSIS
    Date: 2010
    Issue Date: 2012-03-27 17:02:56 (UTC+8)
    Publisher: 國立中央大學
    Abstract: Information about the factors that lead to the deterioration of bridges is essential for bridge maintenance. Pinpointing what these factors are will certainly enhance the effectiveness of bridge management. However, a review of the literature reveals that such factors are mainly determined based on experts' opinions rather than a systematic approach. In this study the factors leading to deterioration of RC bridge decks are grouped into six common types. Twenty-nine candidate factors are selected from an extensive review of past work as well as from the inventory of the Taiwan Bridge Management System. A data mining technique, the Rough Set Theory (RST), is employed to find the factors that have the most significant impact on deterioration. It is found that weather-related factors are rather significant for almost all types of deterioration. Finally, the factors mined by RST are compared to those obtained by Mann-Whitney U (MWU). The results of comparison appear fairly consistent, which validates the proposed approach.
    Relation: COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
    Appears in Collections:[營建管理研究所 ] 期刊論文

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