A Novel Neural Network Training Algorithm for the Identification of Nonlinear Static Systems: Artificial Bee Colony Algorithm Based on Effective Scout Bee Stage

In this study, a neural network-based approach is proposed for the identification of nonlinear static systems. A variant called ABCES (ABC Based on Effective Scout Bee Stage) introduced network training. Two important changes are carried out with ABCES. The first an update “limit” control parameters. ABC algorithm, value fixed. It adaptively adjusted according to number iterations in way, efficiency scout bee stage increased. Secondly, new solution-generating mechanism proposed. solutions created randomly. aimed at developing previous performance analyzed two different problem groups. First, its evaluated 13 numerical benchmark test problems. results compared ABC, GA, PSO and DE. Next, trained by identify 6 problems used. training HS. show that generally effective systems based networks.