An RBF neural network based on improved black widow optimization algorithm for classification and regression problems - Liu, Hui; Zhou, Guo; Zhou, Yongquan; Huang, Huajuan; Wei, Xiuxi (Frontiers in Neuroinformatics, 2023)
In this paper, a radial basis function neural network (RBFNN) based on improved black widow optimization algorithm (IBWO) has been developed, is called IBWO-RBF model. In order to enhance the generalization ability of the IBWO-RBF neural network, the algorithm is designed with nonlinear time-varying inertia weight. Several classification and regression problems are utilized to verify the performance of IBWO-RBF model. In the first stage, the proposed model is applied to UCI dataset classification, nonlinear function approximation and nonlinear system identification; in the second stage, the model solves the practical problem of power load prediction. Compared with other existing models, the experiments show that the proposed IBWO-RBF model achieves both accuracy and parsimony in various classification and regression problems.