期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：10
页码：1-10
出版社：SERSC
摘要：Centripetal Accelerated Particle Swarm Optimization (CAPSO) is a recent and well embraced, interest stimulating topic in swarm intelligence (SI). The original CAPSO method does not have parameters to tune or adjust, so two new parameters are introduced to catapult the efficiency and boost the overall performance. For further enhancement of the algorithm’s efficiency, the principle of quantum-behaved particles is also added. In evaluating the capability of the Improved Centripetal Accelerated Particle Swarm Optimization (ICAPSO) algorithm, we tested it on medical image database, in the aspect of Relevance Feedback of a Content-Based Image Retrieval (CBIR) system, clearly, ICAPSO outperformed others.
