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In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic because probabilities must add to one. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory.
| Autorius: | James J. Buckley |
| Serija: | Studies in Fuzziness and Soft Computing |
| Leidėjas: | Physica-Verlag HD |
| Išleidimo metai: | 2012 |
| Knygos puslapių skaičius: | 180 |
| ISBN-10: | 364286788X |
| ISBN-13: | 9783642867880 |
| Formatas: | 235 x 155 x 11 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Fuzzy Probabilities: New Approach and Applications“
