The strategy of building a flood forecast model by neuro-fuzzy network
學年 94
學期 2
出版（發表）日期 2006-04-01
作品名稱 The strategy of building a flood forecast model by neuro-fuzzy network
作品名稱（其他語言）
著者 Chen, Shen-hsien; Lin, Yong-huang; 張麗秋; Chang, Li-chiu; Chang, Fi-john
單位 淡江大學水資源及環境工程學系
出版者 Bognor Regis: John Wiley & Sons Ltd.
著錄名稱、卷期、頁數 Hydrological processes 20(7), pp.1525-1540
摘要 A methodology is proposed for constructing a flood forecast model using the adaptive neuro-fuzzy inference system (ANFIS). This is based on a self-organizing rule-base generator, a feedforward network, and fuzzy control arithmetic. Given the rainfall-runoff patterns, ANFIS could systematically and effectively construct flood forecast models. The precipitation and flow data sets of the Choshui River in central Taiwan are analysed to identify the useful input variables and then the forecasting model can be self-constructed through ANFIS. The analysis results suggest that the persistent effect and upstream flow information are the key effects for modelling the flood forecast, and the watershed's average rainfall provides further information and enhances the accuracy of the model performance. For the purpose of comparison, the commonly used back-propagation neural network (BPNN) is also examined. The forecast results demonstrate that ANFIS is superior to the BPNN, and ANFIS can effectively and reliably construct an accurate flood forecast model.
關鍵字 flood forecast;neuro-fuzzy;artificial neural network;BPNN;ANFIS
語言 en
ISSN 0885-6087
期刊性質 國外
收錄於 SCI EI
產學合作
通訊作者
審稿制度
國別 GBR
公開徵稿
出版型式 電子版
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