基于粗糙集和多Agent系统的知识挖掘

通过优化知识表达系统中条件属性对决策属性的依赖度,深入研究了粗糙集并与多Agent系统相结合。利用离散粒子群算法,提出一种基于粒子群优化的粗糙集知识约简算法,该算法解决了启发式算法无法全局搜索进行约简的问题。最后通过在矿井中调度信息的应用验证了有效性。

According to the support degree of the knowledge supplied by condition attribute for the whole decision and discrete particle swarm algorithm,connection with the multi agent system.We propose a new algorithm for knowledge reduction in rough set based on particle swarm optimization.The experimental result shows that this algorithm can solve some problems that the existing heuristic algorithm can t solve.Finally we tested our algorithm on dispatching data sets at an underground mine,the experiment results sho...