Hybrid, fuzzy and neural adaptation in case-based reasoning system for process equipment selection

Adaptation is the most difficult step in case-based reasoning. There are no general methods for the modification of the retrieved cases to fit the actual design problem. The use of new, context independent technique is an important research subject. In the paper, a hybrid adaptation system is proposed. Its main components are based on fuzzy logic and neural networks. The applicability of the proposed adaptation methods is examined in preliminary design of mixing system.