Effective search methods for pattern matching inferencing using specific similarity measures
- 2 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Pattern matching inferencing (PMI) is one of the ways of approximating the compositional rule of inference (CRI) as proposed by L. A. Zadeh (1973). PMI is a generic algorithm to create different approximate inferencing algorithms. In particular, approximate analogical reasoning, approximate deductive reasoning and approximate analogical and deductive reasoning are under the class of PMI. PMI as extended by C. Lucas and I. G. Turksen (1990) and the search methods currently used in PMI are considered. Several similarity measures are shown to have some desired properties to make the search process to fire rules in PMI more effective. Using these properties, two new search strategies are proposed instead of the commonly used exhaustive search.Keywords
This publication has 7 references indexed in Scilit:
- Fuzzy logic in control systems: fuzzy logic controller. IIEEE Transactions on Systems, Man, and Cybernetics, 1990
- Fuzzy logicComputer, 1988
- An approximate analogical reasoning approach based on similarity measuresIEEE Transactions on Systems, Man, and Cybernetics, 1988
- Measures of similarity among fuzzy concepts: A comparative analysisInternational Journal of Approximate Reasoning, 1987
- Interval valued fuzzy sets based on normal formsFuzzy Sets and Systems, 1986
- Features of similarity.Psychological Review, 1977
- Outline of a New Approach to the Analysis of Complex Systems and Decision ProcessesIEEE Transactions on Systems, Man, and Cybernetics, 1973