Fuzzy-neural theory applied to Web-based proactive service
In order to realize proactive service, we design and improve relative fuzzy-neural approaches. Generally, the network can be classified into two. One is that fuzzy logic reasoning is completed by fuzzy weight in neural system. The other is that the input data must be fuzzified in the first or second level, but not weight. We discuss and study the second sort fuzzification in this paper. For proactive decision, fusion method based on fuzzy-neural can make Web-based intelligent system keep advantage of fuzzy logic system and remain adaptive optimum in proactive/attentive service. The correctness and validity of our new approach have been tested.