An improved grey wolf optimizer for training q-Gaussian Radial Basis Functional-link nets

Abstract

In this paper, a novel meta-heuristic technique an improved Grey Wolf Optimizer (IGWO) which is an improved version of Grey Wolf Optimizer (GWO) is proposed. The performance is evaluated by adopting the IGWO to training q-Gaussian Radial Basis Functional-link nets (qRBFLNs) neural networks. The function approximation problems in regression areas and the multiclass classification problem in classification areas are employed to test the algorithm. For instance, in order to overcome the multiclass classification problem, the dataset of the screening risk groups of the population age 15 years and over in Charoensin District, Sakon Nakhon Province, Thailand is used in the experiments. The results of the function approximation problems and real application in multiclass classification problem prove that the proposed algorithm is able to address the test problems. Moreover, the proposed algorithm obtains competitive performance compared to other meta-heuristic methods.

Modified Discrete Grey Wolf Optimizer Algorithm for Multilevel Image Thresholding

“…Compared to well-known heuristics such as PSO, GSA, DE, EP, and ES [35–38], the GWO algorithm shows better convergence and higher local optima avoidance. In 2014, Muangkote et al [39] proposed an improved grey wolf optimizer method (IGWO). The strategy on parameter selection of IGWO improves the search capability and the hybridization strategy increases the diversity of the agent.…”

Solution of non-convex economic load dispatch problem using Grey Wolf Optimizer

“…Ghazzai et al [62,63] applied GWO for cell planning problem for the fourth-generation (4G) LTE cellular networks. Muangkote et al [64] proposed Improved Grey Wolf Optimizer for evaluated by adopting the IGWO to training q-Gaussian Radial Basis Functional-link nets (qRBFLNs) neural networks.…”

Automatic generation control of a multi-area ST – Thermal power system using Grey Wolf Optimizer algorithm based classical controllers

“…But its ability is still somewhat dependent or limited on some of the mechanisms in the balance between exploration and exploitation. Recently the improved version of GWO (IGWO) is introduced by Muangkote et al [19]. Like GWO, IGWO recently some new algorithms such as Ant Lion Optimizer (ALO), Multi Verse Optimizer (MVO) are proposed by authors in [20] and [21].…”