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  1. National Taiwan Ocean University Research Hub

Newly Data Classification Techniques in the Development of the Optimal Real-Time Quantitative Precipitation Forecasting Model during Typhoon Periods (II)

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Project title
Newly Data Classification Techniques in the Development of the Optimal Real-Time Quantitative Precipitation Forecasting Model during Typhoon Periods (II)
Code/計畫編號
NSC97-2111-M464-001
Translated Name/計畫中文名
新近資料分類技術應用於最佳颱風即時定量降水預報模式之研發(II)
 
Project Coordinator/計畫主持人
Chih-Chiang Wei
Funding Organization/主管機關
National Science and Technology Council
 
Department/Unit
Department of Marine Environmental Informatics
Website
https://www.grb.gov.tw/search/planDetail?id=1665570
Year
2008
 
Start date/計畫起
01-08-2008
Expected Completion/計畫迄
01-07-2009
 
Bugetid/研究經費
455千元
 
ResearchField/研究領域
大氣科學
 

Description

Abstract
本計畫擬以兩年為期發展一最佳陸上颱風即時定量降水預報模式,此模式預 報內容包括小時降水量(或短時3/6/12/24 小時累積降水量)及總降水量,以提 供水庫現行運用要點防洪運轉時所需之具時效性及高準確性之預測降水量。本研 究將以兩新近資料探勘之規則萃取技術分別建立兩個颱風即時降水預報模式,此 兩技術分別為決策樹演算法與模糊決策樹演算法。 本計畫之工作流程包括八大項,包括颱風資料收集與分析、歷史事件選定與 分類、線性迴歸雨量預報模式建立、決策樹雨量預報模式建立、簡易統計預報模 式建立、模糊決策樹雨量預報模式建立、四種颱風降雨量預報模式比較以及最佳 即時定量降水預報模式評估與應用等八項主要工作。其中資料收集將包括陸上雨 量站雨量資料以及中央氣象局颱風期間各時段即時發佈之海上陸上颱風警報單 內氣象資訊(即颱風中心氣壓、中心位置、暴風半徑、颱風預測速度與方向、中 心最大風速、颱風預測位置等資料)。本計畫擬以台灣北部兩重要水庫(石門及 翡翠水庫)所屬淡水河流域為研究範例,初步擬訂降水測站為流域內之台北雨量 站(或上游集水區測站)為集水區降水預報代表站。 We are proposing a two-year project. The major purpose of the project is to develop optimal real-time quantitative precipitation forecasting (QPF) model during typhoon periods. To provide the optimal real-time precipitations for operators on a reservoir flood-control system during typhoon, we propose the methodology to extract a set of optimal rules for forecasting precipitation. The results obtained from the optimal QPF model include the forecast of hourly rainfall (or 3-/6-/12-/14-hour accumulated rainfall) and total precipitation during typhoon periods. The two newly data mining technologies, namely decision-tree algorithm (ID3) and fuzzy decision-tree algorithm (FIDs) are employed in the extracting rules. The tasks to be carried out can be grouped into the following eight general categories: (1) collection of typhoon data, (2) selection and classification of the typhoon patterns, (3) building of the linear regression rainfall forecasting model, (4) building of the ID3 rainfall forecasting model, (5) building of the simple statistics rainfall forecasting model (such as climatology average method), (6) building of the FIDs rainfall forecasting model, (7) comparison of these four developed models, and (8) selection and application of the optimal real-time QPF model. The collected data involve the precipitations at rainfall station and the typhoon real-time warning document issued by Central Weather Bureau (the content including the data of pressure in the typhoon center, position of typhoon center, the radius of typhoon, the predicted moving speed and direction, the center maximum wind speed, and the predicted typhoon path). The developed methodology will be applied to establish the real-time optimal QPF model in Taipei rainfall station (or reservoir upstream stations) for the Shihmen and Feitsui reservoirs in the Tanshui river basin.
 
Keyword(s)
颱風
定量降水預報
決策樹
模糊理論
資料探勘
typhoon
QPF
decision tree
fuzzy theory
data mining
 
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