Modelling Stable Alluvial River Profiles Using Back Propagation-Based Multilayer Neural Networks

A Novel Comprehensive Evaluation Method for Estimating the Bank Profile Shape and Dimensions of Stable Channels Using the Maximum Entropy Principle

“…So far, many studies have been carried out to examine channel dimensions in dynamic equilibrium state [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. However, few studies have examined the bank profile shape of threshold channels or the static equilibrium of channels.…”

Prediction of channel sinuosity in perennial rivers using Bayesian Mutual Information theory and support vector regression coupled with meta-heuristic algorithms

“…Other soft computing models, namely Support Vector Machine (SVM) and Adaptive Neuro-Fuzzy Inference System (ANFIS), were used for the prediction of alluvial channel patterns and their roughness coefficients (Beechie and Imaki, 2014;Moharana and Khatua, 2014). Several studies adopting soft computing approaches in alluvial channels focused on prediction of the flow field in curved channels, the stable river profile, and width, and the threshold channel bank profile (Baghalian et al, 2012;Bonakdari et al, 2019;Gholami et al, 2019aGholami et al, , 2019bGholami et al, , 2018Shaghaghi et al, 2017;Tahershamsi et al, 2012). Another study (Pham et al, 2019) assessed the variation of the river in Da Dien Estuary, Vietnam using different techniques such as Logistic Regression, Neural Networks, Bootstrap AdaBoost, LogitBoost, bagging, and random subspace.…”