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    Please use this identifier to cite or link to this item: http://chur.chu.edu.tw/handle/987654321/26641


    Title: 遙測地表判釋技術-以竹東為例
    Authors: 陳莉
    Chen, Li
    Contributors: 土木工程學系
    Civil Engineering
    Keywords: 遙感探測;高斯最大似然分類法;倒傳遞類神經網路;影像分類
    Remote Sensing;Maximum- likelihood Decision Rule;Back-propagation Neural Network;Imagery Classification
    Date: 2003
    Issue Date: 2014-06-26 20:43:11 (UTC+8)
    Abstract: 本研究選擇水利會之竹東工作站為研究區域。主要以高斯最大似然分類法
    （maximum- likelihood decision rule ）和倒傳遞類神經網路 (back-propagation neural
    network )兩種人工智慧進行影像分類，其訓練程序由地面調查可能之耕作面積和由影像
    分類所判釋之面積兩者互相比較。本研究所利用之監督分類方法具有高度之準確性可證
    明其精確度。此外，這兩種方法可根據影像分類和生長及收成之圖像能協助我們計算每
    一農作物所需之水量。
    The Chu-tung Working Station of Irrigation Association was selected as the study area.
    This study is aimed at imagery classification by the maximum- likelihood decision rule and
    back-propagation neural network (BPN), both belong to artificial intelligence
    Appears in Collections:[Department of Civil Engineering] Seminar Papers

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