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In this paper, the methodology of using adaptive neuro-fuzzy inference systems (ANFIS) for flood quantile estimation at ungauged sites is presented. The proposed approach has the system identification and interpretability of fuzzy models and the learning capability of artificial neural networks (ANNs). The structure of the ANFIS is identified using the subtractive clustering algorithm. A hybrid learning...
In order to improve the real time forecasting of foods, this paper proposes a modified Takagi Sugeno (T–S) fuzzy inference system termed as threshold subtractive clustering based Takagi Sugeno (TSC-T–S) fuzzy inference system by introducing the concept of rare and frequent hydrological situations in fuzzy modeling system. The proposed modified fuzzy inference systems provide an option of analyzing...
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