Abstract
The paper presents an effective identification method in fuzzy relational systems. We propose an algorithm for constructing models on the basis of fuzzy and nonfuzzy data with the aid of fuzzy discretization and clustering techniques. The usefulness of the method provided is demonstrated by means of two numerical examples. Also a possible way of generating a linguistic decision-making algorithm is discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 153-167 |
| Number of pages | 15 |
| Journal | Fuzzy Sets and Systems |
| Volume | 13 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Jul 1984 |
Keywords
- Clustering techniques
- Fuzzy discretization
- Fuzzy relational system
- Identification algorithm
ASJC Scopus subject areas
- Logic
- Artificial Intelligence
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