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  <titleInfo>
    <title>Applications of Kalman filter techniques in river forecasting</title>
  </titleInfo>
  <name type="personal">
    <namePart>Lee, Shyh-tsai</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Huynh, Ngoc Phien</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Kanchit Malaivongs</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Gupta, Ashim Das</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>Republic of China</namePart>
    <role>
      <roleTerm type="text">Scholarship Donor</roleTerm>
    </role>
  </name>
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  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">th</placeTerm>
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    <place>
      <placeTerm type="text">Bangkok</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>1985</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>78 p.</extent>
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  <abstract>In recent year, Kalman filter techniques have been extensively developed and widely used in many hydrologic forecasting applications. In this study, three useful algorithms of Kalman filter were considered and their forecasting performances were compared. From several runs, it was found that a more complicated and generalized algorithm did not seem to perform better than a simple one. Therefore, a very simple algorithm was adopted throughout the work. The applications considered here involve forecasting of flood flows and forecasting of daily discharge. In the first case, trial-and-error procedures were used to arrive at suitable models which are very simple in its structure. In the second case, an extension of the Linear perturbation (or Hybrid) Model was proposed, where the departure (from the daily mean, or harmonic mean, ) of daily river discharge was linearly regressed upon its past values and past values of the departure of daily rainfall. For all the stations considered, This proposed model produced very good forecasts which were much better than those provided by the original Linear Perturbation Model. It was also found that Kalman filter techniques were not really needed in forecasting daily discharge at these stations.</abstract>
  <note>A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Engineering and Technology</note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 1985</note>
  <subject authority="lcsh">
    <topic>Kalman filtering</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Hydrological forecasting</topic>
  </subject>
  <relatedItem type="series">
    <titleInfo>
      <title>Thesis ; no. CA-85-7</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=B19973</identifier>
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    <url displayLabel="Full-Text">http://203.159.5.9/ait-thesis/detail.php?q=B19973</url>
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