Neural networks and fuzzy logic have some common features such as distributed representation of knowledge, ability to handle data with uncertainty and imprecision etc. Fuzzy logic has tolerance for imprecision of data, while neural networks have tolerance for noisy data. A neural networks learning capability provides a good way to adjust experts knowledge and it automatically generates additional fuzzy rules and membership functions to meet certain specifications. This reduces the design time and cost. On the other hand, the fuzzy logic approach enhances the generalization capability of a...