Hybrid fuzzy connectionist rule-based systems and the role of fuzzy rules extraction

The paper presents the major principles of building complex hybrid systems for knowledge engineering where at the centre of the design process is the task of learning (extracting) fuzzy rules from data. An experimental environment FuzzyCOPE, which facilitates this process, is described. It consists of fuzzy rules extraction module, neural networks module, fuzzy inference methods module and a production rules module. Such an environment makes possible using all of the three paradigms, i,e. fuzzy rules, neural networks and symbolic production rules in one system. Automatic rules extraction from data and choosing the most appropriate reasoning mechanism is also provided. Using FuzzyCOPE for building hybrid systems for decision making and speech recognition is discussed and illustrated