Amirkabir University of TechnologyAmirkabir Journal of Civil Engineering2588-297X53320210522The Study of Energy Dissipation Due to the Use of Vertical Screen in the Downstream of Inclined Drops by Adaptive Neuro-Fuzzy Inference System (ANFIS)The Study of Energy Dissipation Due to the Use of Vertical Screen in the Downstream of Inclined Drops by Adaptive Neuro-Fuzzy Inference System (ANFIS)921934356310.22060/ceej.2019.16694.6305FARezaNorouzi SarkarabadDepartment of water engineering, Tabriz University, Tabriz, Iran.0000-0002-3756-8746RasoulDaneshfarazDepartment of Civil Engineering, Faculty of Engineering, University of Maragheh, Iran.0000-0003-1012-8342AliBazyarDepartment of Civil Engineering, Faculty of Engineering, University of Maragheh, Iran.Journal Article20190705The aim of the current study, investigate the energy dissipation of the use of the vertical screen with two porosity ratios downstream of the inclined drop with three different angles, two heights of the drop, and the range of 200-700 l/min with an analysis of 140 laboratory models. The results revealed that the use of screens caused by an increase of at least 407% and a maximum of 903% of total relative energy dissipation efficiency to the plain inclined drop. The equations were presented to estimate the relative energy dissipation due to the use of a vertical screen downstream of the inclined drop with acceptable assessment criteria. Also, the contribution of each of the energy dissipation systems was presented. Then, intelligent models, Artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) were compared to estimate the relative energy dissipation using three parameters θ, P, and y<sub>c</sub>/∆z using evaluation criteria. The values of R2 and RMSE for the ANFIS model, were 0.996 and 0.006, respectively, and for the ANN model were 0.992 and 0.008 respectively, which revealed the higher accuracy of the ANFIS model in the estimation of the relative energy dissipation than the ANN.The aim of the current study, investigate the energy dissipation of the use of the vertical screen with two porosity ratios downstream of the inclined drop with three different angles, two heights of the drop, and the range of 200-700 l/min with an analysis of 140 laboratory models. The results revealed that the use of screens caused by an increase of at least 407% and a maximum of 903% of total relative energy dissipation efficiency to the plain inclined drop. The equations were presented to estimate the relative energy dissipation due to the use of a vertical screen downstream of the inclined drop with acceptable assessment criteria. Also, the contribution of each of the energy dissipation systems was presented. Then, intelligent models, Artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) were compared to estimate the relative energy dissipation using three parameters θ, P, and y<sub>c</sub>/∆z using evaluation criteria. The values of R2 and RMSE for the ANFIS model, were 0.996 and 0.006, respectively, and for the ANN model were 0.992 and 0.008 respectively, which revealed the higher accuracy of the ANFIS model in the estimation of the relative energy dissipation than the ANN.https://ceej.aut.ac.ir/article_3563_09b873f6b563c28fe144d10c8cf9582a.pdf