摘要
为了提高模糊产生式规则的知识表示能力,人们在模糊产生式规则中引入了局权、全权、置信度等参数。视加权模糊规则中的权重等为可调的知识表示参数,首先研究这些知识表示参数与加权模糊规则的泛化能力之间的关系,然后提出了一种基于极大模糊熵原理的知识表示参数优化方法。在选定数据集上的仿真实验数据表明,提出的方法可以明显提高基于加权模糊产生式规则的专家推理系统的泛化能力。
In order to improve the capability of knowledge representation of fuzzy production rules, several parameters such as local weight, global weight and certainty factor have been incorporated into the fuzzy production rules. Regarding the weights and certainty factors as adjustable parameters, firstly, the relationship between these adjustable parameters and the generalization capability is explored. Secondly, a new rule refinement scheme based on the well known fuzzy entropy maximization is proposed. Experimental results on a number of selected databases demonstrate the expected improvement of generalization capability of the FPR-based expert systems.
出处
《科学技术与工程》
2006年第5期534-539,共6页
Science Technology and Engineering
基金
国家自然科学基金(60473045
60573069)资助
关键词
加权模糊产生式规则
泛化能力
模糊推理
极大模糊熵原理
weighted fuzzy production rules generalization capability fuzzy reasoning maximization principle fuzzy entropy
