en Numerical Investigation مقاله پژوهشي Research Paper <span style="font-size:12pt"><span style="line-height:200%"><span new="" roman="" style="font-family:" times=""><span style="color:black">Developing vegetation cover is one of the practical solutions to alleviate the sediment transfer rate. Predicting the sediment transfer rate in the presence of cover vegetation is a complicated necessary issue for designers due to the complex interaction between sediments and cover vegetation. This study intends to predict the sediment transfer rate (STR) by employing soft computing models based on an experimental study. The </span><span style="line-height:200%"><span style="color:black">primary</span></span><span style="color:black"> innovations </span><span style="line-height:200%"><span style="color:black">in this</span></span><span style="color:black"> study were the introduction of new and optimized versions of </span><span style="line-height:200%"><span style="color:black">the </span></span><span style="color:black">group method of data handling (GMDH) for predicting sediment transport rate, </span><span style="line-height:200%"><span style="color:black">the use of</span></span><span style="color:black"> a new inclusive multiple model for predicting sediment transport rate, and </span><span style="line-height:200%"><span style="color:black">the investigation of </span></span><span style="color:black">the effects of </span><span style="line-height:200%"><span style="color:black">various</span></span><span style="color:black"> parameters </span><span style="line-height:200%"><span style="color:black">on the sediment transport rate, </span></span><span style="color:black">such as vegetation cover density</span><span style="line-height:200%"><span style="color:black">.</span></span><span style="color:black"> This study used an inclusive multiple model (IMM) as an ensemble model to predict sediment transport in the presence of cover vegetation. </span><span style="line-height:200%"><span style="color:black">Initially</span></span><span style="color:black">, the </span><span style="line-height:200%"><span style="color:black">sediment transport rate was predicted using the </span></span><span style="color:black">individual GMDH models</span><span style="line-height:200%"><span style="color:black">. </span></span><span style="color:black">These outputs were </span><span style="line-height:200%"><span style="color:black">then used to create the final outputs by inserting them</span></span><span style="color:black"> into the GMDH model as an ensemble model </span><span style="line-height:200%"><span style="color:black">at</span></span><span style="color:black"> the next level</span><span style="line-height:200%"><span style="color:black">.</span></span><span style="color:black"> The Honey Badger algorithm (HBA), </span><span style="line-height:200%"><span style="color:black">the </span></span><span style="color:black">rat swarm optimization algorithm (RSOA), </span><span style="line-height:200%"><span style="color:black">the </span></span><span style="color:black">sine cosine algorithm (SCA), and </span><span style="line-height:200%"><span style="color:black">the </span></span><span style="color:black">particle swarm optimization algorithm (PSOA) were used to train the GMDH model. </span><span style="line-height:200%"><span style="color:black">The diameter</span></span><span style="color:black"> of the sediments, </span><span style="line-height:200%"><span style="color:black">the</span></span><span style="color:black"> diameter</span><span style="line-height:200%"><span style="color:black"> of the stems, the density of</span></span><span style="color:black"> vegetation cover</span><span style="line-height:200%"><span style="color:black">, the</span></span><span style="color:black"> wave height, </span><span style="line-height:200%"><span style="color:black">the </span></span><span style="color:black">wave velocity, </span><span style="line-height:200%"><span style="color:black">the </span></span><span style="color:black">cover height</span><span style="line-height:200%"><span style="color:black">,</span></span><span style="color:black"> and </span><span style="line-height:200%"><span style="color:black">the </span></span><span style="color:black">wave force were used as inputs to the models. The IMM&#39;s mean absolute error (MAE) was 0.145 m3/s</span><span style="line-height:200%"><span style="color:black">,</span></span><span style="color:black"> while </span><span style="line-height:200%"><span style="color:black">the MAEs for</span></span><span style="color:black"> GMDH-HBA, GMDH-RSOA, GMDH-SCA, GMDH-PSOA, and GMDH in the testing level</span><span style="line-height:200%"><span style="color:black"> were 0.176 m3/s, 0.312 m3/s, 0.367 m3/s, 0.498 m3/s, and 0.612 m3/s, respectively. The </span></span><span style="color:black">Nash&ndash;Sutcliffe </span><span style="line-height:200%"><span style="color:black">coefficient (NSE)</span></span><span style="color:black"> of IMM, GMDH-HBA, GMDH-RSOA, GMDH-SCA, GMDH-PSOA, and GHMDH </span><span style="line-height:200%"><span style="color:black">were</span></span><span style="color:black"> 0.95 0.93, 0.89, 0.86, 0.82, and 0.76, respectively. </span><span style="line-height:200%"><span style="color:black">Additionally, this</span></span><span style="color:black"> study </span><span style="line-height:200%"><span style="color:black">demonstrated</span></span><span style="color:black"> that </span><span style="line-height:200%"><span style="color:black">vegetation cover decreased sediment transport rate by 90%.</span></span><span style="color:black"> The </span><span style="line-height:200%"><span style="color:black">overall</span></span><span style="color:black"> results indicated that the IMM and GMDH-HBA </span><span style="line-height:200%"><span style="color:black">models could accurately predict</span></span><span style="color:black"> sediment transport </span><span style="line-height:200%"><span style="color:black">rates</span></span><span style="color:black">. </span></span></span></span><br> &nbsp; Sediment transport rate,Coastal regions,Forest cover,Group method of data handling,Optimization Algorithms 26 50 http://ijmt.ir/browse.php?a_code=A-10-811-2&slc_lang=en&sid=1 elham Ghanbari Adivi elhamgh44@gmail.com 10031947532846004241 10031947532846004241 Yes Associated professor, Shahrekord university