点击次数：

论文类型：期刊论文

发表时间：2012-07-01

发表刊物：WATER SCIENCE AND TECHNOLOGY

收录刊物：SCIE、EI、PubMed、Scopus

卷号：66

期号：10

页面范围：2090-2098

ISSN号：0273-1223

关键字：association rule analysis; flood forecasting; fuzzy reasoning

摘要：In this paper, a computationally efficient version of the widely used Takagi-Sugeno (T-S) fuzzy reasoning method is proposed, and applied to river flood forecasting. It is well known that the number of fuzzy rules of traditional fuzzy reasoning methods exponentially increases as the number of input parameters increases, often causing prohibitive computational burden. The proposed method greatly reduces the number of fuzzy rules by making use of the association rule analysis on historical data, and therefore achieves computational efficiency for the cases of a large number of input parameters. In the end, we apply this new method to a case study of river flood forecasting, which demonstrates that the proposed fuzzy reasoning engine can achieve better prediction accuracy than the widely used Muskingum-Cunge scheme.