Title :
On the construction of hierarchical fuzzy systems models
Author :
Yager, Ronald R.
Author_Institution :
Machine Intelligence Inst., Iona Coll., New Rochelle, NY, USA
fDate :
2/1/1998 12:00:00 AM
Abstract :
A review of the basic ideas of fuzzy systems modeling is provided. We introduce a hierarchical-type fuzzy systems model called a hierarchical prioritized structure (HPS) and review its structure, operation, and the interlevel aggregation algorithm. We then turn to the issue of constructing the HPS. Consideration is first given to the case in which rules are provided by an expert. Detailed consideration is given to the problem of completing incomplete priorities by use of the principle of maximal buoyancy. A mathematical programming method is introduced for the implementation of this approach. The issue of tuning hierarchical models is addressed. We next introduce a dynamic approach to the formulation of an HPS directly from data that enables us to continually update our model as more observations become available. This approach allows a system´s builder to start with a default model and include exceptions
Keywords :
fuzzy systems; hierarchical systems; learning systems; mathematical programming; modelling; continual model updating; default model; exceptions; hierarchical fuzzy systems model construction; hierarchical model tuning; hierarchical prioritized structure; incomplete priorities; interlevel aggregation algorithm; learning; mathematical programming; maximal buoyancy; priority; rules; Aggregates; Control system synthesis; Entropy; Fuzzy logic; Fuzzy systems; Machine intelligence; Mathematical model; Mathematical programming; Modeling; Probability distribution;
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
DOI :
10.1109/5326.661090