Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves
學年 93
學期 2
出版（發表）日期 2005-04-30
作品名稱 Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves
作品名稱（其他語言）
著者 Chang, Ya-ting; 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 19(7), pp.1431-1444
摘要 To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network-based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M-5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input–output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M-5 curves in real-time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved.
關鍵字 genetic algorithm;artificial neural network;fuzzy rule base;adaptive network-based fuzzy inference system;reservoir operation
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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