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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/5785

    Title: Discovery of Temporal Variation of Arsenic in a Historical Blackfoot Disease Territory by Time Series Analysis
    Authors: Jan-Yee Lee(李詹儀)
    Ting-Nien Wu
    Keywords: groundwater management
    water quality
    time series analysis
    data mining
    Date: 2009
    Issue Date: 2009-11-18 09:02:48 (UTC+8)
    Abstract: Time series analysis is useful tool for extracting
    interesting pattern from ordered sequence of
    observations. The Chianan Blackfoot disease region
    was selected as study area, and the monitoring data
    of arsenic in groundwater during the period of 2003
    and 2008 was subjected to time series analysis. This
    study attempted to discover the temporal trend of
    arsenic level in groundwater by applying the tool of
    time series analysis. ARMA and ARIMA, the common
    time series modelling methods, were employed to
    interpret the information beneath the monitoring
    data of groundwater quality. Through further
    verification, the selected ARMA(1,1) model fits the
    data set well over the other three models. The result
    showed that this developed numerical model can
    effectively interpret and forecast the arsenic level in
    groundwater from area affected by salinization and
    high arsenic level in Chianan Plain based on the
    known information.
    Appears in Collections:[環境工程系所] 期刊論文

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