文章基本信息

标题：ANALYSIS OF HYBRID METAHEURISTIC TECHNIQUES ON CLASSIFICATION
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作者：ANJU BALA ; PRITI
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：16
页码：4334-4344
出版社：Journal of Theoretical and Applied
摘要：This paper discusses different hybrid version of Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Differential Evaluation (DE) and Genetic Algorithm (GA) and analyzes the performance of different hybrid algorithms in terms of classification accuracy. The hybridization is done to remove the limitations of each individual technique by incorporating the advantages of other techniques resulting in better convergence towards global optima. The paper covers various hybrid meta-heuristic techniques including ACO-PSO, ACO-GA, PSO-GA, GA-DE, and ACO-PSO-GA. The analysis has been done on different datasets downloaded from UCI repository using the parameters classification accuracy, sensitivity and specificity. The analysis clearly shows the impact of the hybridization on the classification in terms of accuracy as well as sensitivity and specificity.
关键词：ACO; PSO; GA; DE; Hybrid; Classification; Meta;heuristic