Multi-attribute fuzzy rules classification based on cloud-neural network
Zheng Li · Kongzhi yu juece · 2009
For the limitation of hard classification of data borderline in fuzzy rules sort,this paper establishes a cloud-neural network model and gives the arithmetic of fuzzy rules classification.It transforms data information in to rule information while keeps its the efficiency,fuzzy information and randomicity.Then by using the well learning ability of neural networks,the multi-attribute fuzzy rules are realized.Compared with the traditional neural network,these methods improve the precision or efficiency of the model,while keep its fuzzy information,randomicity and the veracity of classifying rules.Finally,this paper uses real flood-drought data to simulate,the result demonstrates its validity and feasibility.