Effective search methods for pattern matching inferencing using specific similarity measures
1992 IEEE International Conference on Fuzzy Systems - FUZZ-IEEE, San Diego, CA, USA, 8 - 12 Mart 1992, ss.161-168, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Basıldığı Şehir: San Diego, CA, USA
- Sayfa Sayıları: ss.161-168
- Boğaziçi Üniversitesi Adresli: Evet
Özet
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.