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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/12651


    Title: 支撐向量機分類器於商業型用戶違章用電之應用
    Authors: 卓明遠;鄭淵澤;王念中;黃佳文
    Contributor: 電機工程系
    Keywords: 商業型用戶違章用電模式;模式辨識技術;支撐向量機
    Commercial customer electricity theft model;Pattern recognition technique;Support vector machine
    Date: 2010-12-03
    Issue Date: 2010-12-16 14:37:56 (UTC+8)
    Publisher: 台南縣:崑山科技大學
    Abstract: 本 論文提出一種支撐向量機( Support Vector Machine,SVM)網路之模型辨識技術,藉由用戶合理用電模型之建立與比對,進行商業型用戶違章用電之分類。首先,本文收集台灣代表性之商業型用戶用電歷史資料,推導其夏月與非夏月之合理用電模型,再者應用支撐向量機網路模型,針對商業型用戶違章用電行為與特性,建立商業型用戶之違章用電分類器,針對各類型用戶進行資料分類與辨識,推求用戶違章用電之模式,並找出有違章用電可能之用戶及其違章用電之度數。
    This thesis proposes support vector machine based pattern recognition technique to classify commercial customer electricity theft by establishing and comparing with the various rational load patterns. First, in this thesis,
    Taiwan commercial customers’ historical electricity data is collected to derive the summer and non-summer reasonable power consumption model. Moreover, the SVM network model is employed to train the selected commercial customer data set to establish the commercial customer electricity theft classifier and then the electricity theft electricity KWH can be derived by analyzing and recognizing historical data in database.
    Relation: 第31屆電力工程研討會
    Appears in Collections:[電機工程系所 ] 2010第卅一屆電力工程研討會

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