稀疏规则条件下的相似插值推理研究

模糊推理本质上就是插值器。但在稀疏规则库的务件下，当输入的事实落入规则“空隙”时，采用传统的CRI方法是得不到任何推理结果的。而采用KH线性插值推理也存在着难以保证推理结果的凸性和正规性等问题。为了在稀疏规则条件下能有好的插值推理结果，提出了一种相似插值推理方法。谊方法能较好地保证推理结果隶属函数的凸性和正规性，这为智能系统中的模糊推理提供了一个十分有用的工具。

Reasearch on Similarity Interpolative Reasoning for the Sparse Fuzzy Rule

Fuzzy reasoning is really equal to a interpolation.But when rule base is sparse, we can not get any reasoning result by traditional CRI method for an observation is in the gap between two neighboring antecedents. It is also difficult to keep convexity and normality using KH linear interpolative reasoning method. In order to get better result when rule base is sparse,we propose a similarity interpolative reasoning method which can keep the convexity and normality of the reasoning result better. It devotes a useful tool for fuzzy reasoning in intelligent systems.