scholarly journals Adaptive neuro-fuzzy interference system modelling for Chlorpyrifos removal with walnut shell biochar

2021 ◽  
pp. 103443
Author(s):  
Şevket Tulun ◽  
Gökçen Akgül ◽  
Alper Alver ◽  
Hakan Çelebi
Keyword(s):  
Walnut Shell ◽  
System Modelling ◽  
Fuzzy Interference System ◽  
Interference System ◽  
Neuro Fuzzy

scholarly journals Estimation of maximum scour depth downstream of an apron under submerged wall jets

2019 ◽  
Vol 21 (4) ◽  
pp. 523-540 ◽  
Author(s):  
Mohammad Aamir ◽  
Zulfequar Ahmad
Keyword(s):  
Scour Depth ◽  
Regression Equations ◽  
Wall Jets ◽  
Statistical Parameters ◽  
Densimetric Froude Number ◽  
Sediment Size ◽  
Fuzzy Interference System ◽  
Interference System ◽  
Neuro Fuzzy ◽  
Artificial Neural Network Ann

Abstract An analysis of laboratory experimental data pertaining to local scour downstream of a rigid apron developed under wall jets is presented. The existing equations for the prediction of the maximum scour depth under wall jets are applied to the available data to evaluate their performance and bring forth their limitations. A comparison of measured scour depth with that computed by the existing equations shows that most of the existing empirical equations perform poorly. Artificial neural network (ANN)- and adaptive neuro-fuzzy interference system (ANFIS)-based models are developed using the available data, which provide simple and accurate tools for the estimation of the maximum scour depth. The key parameters that affect the maximum scour depth are densimetric Froude number, apron length, tailwater level, and median sediment size. Results obtained from ANN and ANFIS models are compared with those of empirical and regression equations by means of statistical parameters. The performance of ANN (RMSE = 0.052) and ANFIS (RMSE = 0.066) models is more satisfactory than that of empirical and regression equations.

Sign in / Sign up

Export Citation Format

Share Document