Rainstorm forecasting by mining heterogeneous remote sensed datasets
Chapter in an edited book (author)

香港中文大學研究人員
替代計量分析
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其它資訊
摘要This chapter presents an automatic meteorological data mining system based on analyzing and mining heterogeneous remote sensed image datasets, with which it is possible to forecast potential rainstorms in advance. A two-phase data mining method employing machine learning techniques, including the C4.5 decision tree algorithm and dependency network analysis, is proposed, by which a group of derivation rules and a conceptual model for metrological environment factors are generated to assist the automatic weather forecasting task. Experimental results have shown that the system reduces the heavy workload of manual weather forecasting and provides meaningful interpretations to the forecasted results. © 2010, IGI Global.
著者Yang Y.-B., Lin H.
編輯ed. by Leon Shyue-Liang Wang & Tzung-pei Hong.
詳細描述ed. by Leon Shyue-Liang Wang & Tzung-pei Hong.
出版年份2010
月份12
日期1
頁次387 - 404
國際標準書號9781615207572
語言英式英語

上次更新時間 2021-17-10 於 23:45