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Fuzzy Modeling in Stochastic Environment: Theory, Knowledge Bases, Examples Anna Walaszek-babiszewska
Fuzzy Modeling in Stochastic Environment: Theory, Knowledge Bases, Examples
Anna Walaszek-babiszewska
The fuzzy sets theory as a tool for modeling offers approximations of imprecisely formulate dependencies, values of variables, functions, and the values of truth. The probability theory and stochastic processes used for fuzzy events enables the determination of the probability of imprecise random events, linguistic random variables or stochastic processes with fuzzy states. In practical modeling, probability is represented by the frequency of applicable fuzzy events, calculated on the grounds of empirical data. The determination of the procedures of reasoning in consideration of the fuzzy logics and fuzzy sets theory is as important as the discussed creation of the structure of knowledge bases. Some of currently used experts systems, especially in medicine or economics, should have an option of updating their fuzzy knowledge bases on the grounds of the collected data. The approach presented in the monograph is a response to such needs.
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 15 de julio de 2011 |
| ISBN13 | 9783845410227 |
| Editores | LAP LAMBERT Academic Publishing |
| Páginas | 144 |
| Dimensiones | 150 × 9 × 226 mm · 233 g |
| Lengua | Alemán |
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