关键词: 粒子群优化, 模糊C-均值, 模糊粗糙集, 属性约简, 信息熵, Particle Swarm Optimization (PSO), Fuzzy C-Means (FCM), fuzzy Rough Set (RS), entropy

Abstract: Considering the problem that PSO algorithm is easy to fall into local optimum, crossover and mutation operators were introduced. The modified PSO algorithm was combined with Fuzzy CMeans (FCM) algorithm and a new fuzzy clustering algorithm (CMPSOFCM) was proposed. The searching capability and clustering effect were improved by this new algorithm. Then the membership matrix obtained by clustering algorithm was used to reduce attribute set. Finally, based on entropy, a knowledge acquisition method of fuzzy Rough Set (RS) was put forward. Experiment and example were provided to verify the effectiveness and practicability of this approach.

Key words: attribution reduction