A Kind of Context-Aware Approach Based on Fuzzy-Neural for Proactive Service of Pervasive Computing

The task-oriented proactive seamless migration is one of difficult problems to be solved in pervasive computing paradigm. Apparently, this function of seamless mobility is suitable for mobile services, such as mobile Web-based learning. But when seamless migration for computing task of learning is realized among PC, laptop, or PDA, there are several difficult problems to be solved, such as how to supply the proactive/attentive service with uncertainty for aware context. In order to realize E-learning based on proactive seamless migration, we design and improve relative fuzzy-neural approach (of course, besides it, there are other 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 in this paper. For proactive decision, fusion method based on fuzzy-neural can make Web-based learning 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.