Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel

Sediment transport is a prevalent vital process in fluvial and coastal environments, and incipient motion is an issue inseparably bound to this topic. this study utilizes a novel hybrid method based on group method of data handling (gmdh) and genetic algorithm (ga) to design gmdh structural (gmdh-ga). also, singular value decomposition (svd) was utilized to compute the linear coefficient vectors. in order to predict the densimetric froude number (fr), the ratio of median diameter of particle size to hydraulic radius (d/r) and the ratio of sediment deposit thickness to hydraulic radius (ts/r) are utilized as effective parameters. using three different sources of experimental data and gmdh-ga model, a new equation is proposed to predict incipient motion. the performance of development equation is compared using gmdh-ga and traditional equations . the results indicate that the presented equation is more accurate (.rmse = 0.18 and mape = 6.48%) than traditional methods. also, a sensitivity analysis is presented to study the performance of each input combination in predicting incipient motion.