Reasearch on Similarity Interpolative Reasoning for the Sparse Fuzzy Rule
稀疏规则条件下的相似插值推理研究

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.