属性约简自寻优算法

AN ADAPTIVE SEARCHING OPTIMAL ALGORITHM FOR THE ATTRIBUTE REDUCTS

属性约简是知识获取中的关键问题之一 .为了能够较为有效地获得较优的属性约简 ,首先在粗糙集理论的基础上构造出了相对差异比较表 ,然后把它与启发性知识相结合分别设计出了 3个算法 :属性约简的改进算法(AR1) ,属性约简判定的完备算法 (RJ)和属性约简的改进增强算法 (AR2 ) ;接着 ,将这些算法作为子算法并吸收了基因算法的基本思想和模拟退火算法的具体操作 ,设计出了属性约简自寻优算法 (ADSOA) ;最后 ,将该算法应用于中医类风湿关节炎诊断决策表的约简 .实验结果表明 ,属性约简自寻优算法能够以较大的概率和较高的效率获得较优的属性约简 ,对于某些具体问题来说甚至能够获得最佳的属性约简 ;

Attribute reduction is one of the key problems for the knowledge acquisition. Based on the rough set theory, the relative difference comparison table is constructed to effectively and efficiently achieve the better attribute reducts. Then the relative difference comparison table is combined with the heuristic knowledge to design three algorithms respectively: the improved algorithm for attribute reducts (AR1), the complete algorithm for judgement of attribute reduct (RJ), and the enhanced algorithm for attribute reducts (AR2). The adaptive searching optimal algorithm for the attribute reducts (ADSOA) is designed by combining the main thoughts of the gene algorithm and the concrete operations of the stimulated annealing strategy with the above three algorithms. And the ADSOA is used to reduce the rheumatoid arthritis diagnosis decision table in the traditional Chinese medicine. The experimentation results show that the ADSOA can obtain the better attribute reducts more effectively and efficiently, and even can achieve the optimal attribute reducts for some specific problems. At the same time, it is concluded that the presence of relative difference comparison tables is practically meaningful for further constructing much more effective and efficient algorithms for the attribute reducts.