Fuzzy expert systems versus neural networks

The authors describe a rule-based fuzzy expert system using a method of approximate reasoning to evaluate the rules when given new data. It is argued that any fuzzy expert system using one block of rules can be approximated. The theory is generalized to networks of neural nets and fuzzy expert systems using multiple interconnected blocks of rules. The authors demonstrate how the neural net is trained, and how the rules in the fuzzy expert system are written. An example illustrating these ideas is presented