Article ID Journal Published Year Pages File Type
406382 Neurocomputing 2015 11 Pages PDF
Abstract

This paper proposes an improved dynamic particle swarm optimization algorithm, which uses a new and effective exponential decreasing inertia weight (EDIW) strategy. Based on the improved EDIW-PSO algorithm together with AdaBoost algorithm, we adjust the parameters (centers, widths, shape parameters and connection weights) of GRBF and present a novel hybrid EDIW-PSO-AdaBoost-GRBF model. Two application examples are given on the proposed model. The results obtained show that the proposed model is effective and feasible for prediction problems.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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