A fast genetic method for inducting descriptive fuzzy models
✍ Scribed by Luciano Sánchez; José Otero
- Book ID
- 104291605
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 311 KB
- Volume
- 141
- Category
- Article
- ISSN
- 0165-0114
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
This paper is concerned with FS-FOIL -an extension of Quinlan's First-Order Inductive Learning Method (FOIL). In contrast to the classical FOIL algorithm, FS-FOIL uses fuzzy predicates and, thereby, allows to deal not only with categorical variables, but also with numerical ones, without the need to
The nature of interference sources in signal processing is a key problem in many applied disciplines. These interferences are often modelled by random processes, although it has been shown that many models can be favourably modified when some of the uncertainty sources are treated as fuzzy experimen
It has been demonstrated many times in practice that fuzzy logic controllers have an important role in rule-based expert systems. However, it is essential for a fuzzy logic controller to have an appropriate set of rules to perform at the desired level. The linguistic structure of the fuzzy logic con
Fuzzy models describe nonlinear input-output relationships with linguistic fuzzy rules. A hierarchical fuzzy modeling is promising for identification of fuzzy models of target systems that have many input variables. In the identification, (1) determination of a hierarchical structure of submodels, (