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  <titleInfo>
    <title>Forecasting of seasonal streamflows</title>
  </titleInfo>
  <name type="personal">
    <namePart>Chen, Ming-an</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Huynh, Ngoc Phien</namePart>
    <role>
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    </role>
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  <name type="personal">
    <namePart>Do, Ba Khang</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Gonzales, Jr. , R. L.</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>R.O.C. Government</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
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    <place>
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    </place>
    <place>
      <placeTerm type="text">Bangkok</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>1994</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>71 leaves</extent>
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  <abstract>In this study, the time series of monthly flows of the Mekong River and ten-day flows of  the Tachia River were used to build forecasting models by using multiple regression analysis, Box Jenkins method and back propagation method. All of the forecasting methods with lead time = 1  and 2 were implemented in this study. It was found that back propagation method can obtain the  best results during calibration period and Box-Jenkins models can get better results than multiple  regression method in most of the cases. For forecasting seasonal flows by back propagation  method, using one hidden layer network is enough to get quite satisfactory results. The forecasting  accuracy for lead time= 2 (time units) is a little worse than that for lead time= 1 as expected.</abstract>
  <note>A thesis submitted in partial fulfillment of the requirement for the degree of Master of Engineering, School of Engineering and Technology</note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 1994</note>
  <subject authority="lcsh">
    <topic>Regression analysis</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Hydraulics</topic>
    <topic>Data processing</topic>
  </subject>
  <relatedItem type="series">
    <titleInfo>
      <title>Thesis ; no. CS-94-10</title>
    </titleInfo>
    <name type="corporate">
      <namePart>Asian Institute of Technology.</namePart>
      <namePart/>
    </name>
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  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B15645</identifier>
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    <url displayLabel="Full-Text">http://203.159.5.9/ait-thesis/detail.php?q=B15645</url>
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