Seyed Hamed Ashraf Talesh

TL;DR: In this article, the adaptive neuro-fuzzy inference system (ANFIS) is employed to model the discharge coefficient in rectangular sharp-crested side weirs.

TL;DR: According to the sensitivity analysis results, the pile diameter and number of piles normal to the flow are the most effective parameters for predicting scour at pile groups in clear water condition and ANFIS-DE/SVD outperforms the other techniques.

TL;DR: This study introduces a new hybrid method that combines an adaptive neuro-fuzzy inference system (ANFIS), Differential Evolution (DE) algorithm and Singular Value Decomposition (SVD) to predict the bank profile of a threshold channel.

TL;DR: In this paper, a pareto evolutionary structure of adaptive neuro-fuzzy inference system (ANFIS) network is presented for abutment scour depth prediction, where the genetic algorithm (GA) and singular value decomposition (SVD) is utilized in optimizing design of nonlinear antecedent parts and linear consequent parts of TSK-type of fuzzy rules simultaneously in ANFIS design.

TL;DR: It can be said that not only DE optimization algorithms have a significant impact on increasing the performance of a simple ANFIS model but also using evolutionary algorithms (ANFIS-DE/SVD) reduce the ANFis-DE model error accordingly.