Predicting the geometry of stable alluvial channels: combination of data mining and meta-heuristic optimization

One of the important topics in river engineering is the design of stable alluvial channel geometry in the regime mode (dynamic balance between erosion and sedimentation) including the width, depth and slope. In this research, the ANFIS and ANFIS-PSO models were used to model the geometry parameters of stable channels. To achieve this objective, we utilized a comprehensive dataset comprising 410 data series sourced from 15 different channels, encompassing various types such as straight and meandering, as well as natural and laboratory. In each measurement, information on the flow rate (Q), average particle diameter (d), shear stress (τ), top width of the channel (W), average depth of flow (h) and longitudinal slope of the channel (S) was collected. Randomly, 70% of the data was used for training, and the remaining 30% was used for validation of the ANFIS and ANFIS-PSO models. Totally, 42 models were derived from the combination of 7 input data sets (Q, d, and τ) and employed both ANFIS and ANFIS-PSO, models to estimate the W, h, and S as the three types of outputs. In modeling of the W and h parameters, the best input was the Q, which the R2, CRM and NRMSE for all data with the ANFIS model were equal to 0.954, -0.029, 0.567 and with ANFIS-PSO model were 0.912, -0.042, and 0.487, respectively. Also, to estimate the S, the modeling results had error. In general, the modeling results with the ANFIS-PSO model were more accurate than the results of the ANFIS model.