群智能方法是新兴的模拟计算技术,在求解复杂的优化问题中表现出良好的性能。对比讨论了群智能的两个重要组成方面(蚁群算法和微粒群算法)在知识发现中的实现方法,阐述了算法的原理和特性,并提出了一些在将来需要解决的问题。
As a novel simulated evolutionary computation technology, swarm intelligence has shown its performance in solving complex optimization problem. This paper introduces and discusses the application of ACO and PSO in Knowledge Discovery in Database(KDD). The basic principle and characteristics of the algorithms are addressed in the paper. Finally, some problems to be solved are mentioned.