摘要
Fuzzy netal network (FNN) is a new tool for extraction of fuzzy control rules from experimental data, butno such rule can be extracted directly from small samples. This paper presents a new approach to fuzzy rules andmembership function for small samples i. e. clustering by the Hebb differential competition rule and extending eachitem of sample information to the control point in its factor space while BP algorithm is applied to the study of factornetwork weights in it. This approach has ben successfully applied to the simulation of rainfall prediction.
Fuzzy netal network (FNN) is a new tool for extraction of fuzzy control rules from experimental data, butno such rule can be extracted directly from small samples. This paper presents a new approach to fuzzy rules andmembership function for small samples i. e. clustering by the Hebb differential competition rule and extending eachitem of sample information to the control point in its factor space while BP algorithm is applied to the study of factornetwork weights in it. This approach has ben successfully applied to the simulation of rainfall prediction.
