원문정보
초록
영어
This paper built a optimization model and proposed an improved firefly optimization algorithm called CFA, which is based on firefly Cooperative. The main idea of CFA is to extend the single population FA to the interacting multi-swarms by cooperative Models. In this work, firstly, CFA algorithm is used for optimizing six widely-used benchmark functions and the comparative results produced by, firefly optimization algorithm(FA) are studied. Secondly, CFA algorithm used in data mining, clustering analysis on several typical data sets. The performance of typical data clustering results showed that the biological heuristic algorithm based on clustering analysis algorithm with the existing success of FA compared to faster convergence, and the clustering of higher quality.
목차
1. Introduction
2. Standard AF algorithm
2.1. Basic Firefly Algorithm
2.2.The FA Algorithm Steps
3. The Cooperative Firefly Algorithm(CFA)
4. Experimental Result
4.1 Benchmark Functions
4.2 Results for the 10-D Problems
4.3 Results for the 20-D Problems
5. Data Clustering Experimental Results
6. Conclusion
Acknowledgements
References