Fuzzy Probabilities [electronic resource] :New Approach and Applications / by James J. Buckley.
by Buckley, James J [author.]; SpringerLink (Online service).
Material type:
BookSeries: Studies in Fuzziness and Soft Computing: 115Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.Description: XII, 164 p. online resource.ISBN: 9783540323884.Subject(s): Computer science | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics)DDC classification: 006.3 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| TJ210.2-211.495 (Browse shelf) | Available | ||||
| Long Loan | MAIN LIBRARY | Q334-342 (Browse shelf) | Available |
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| TA329-348 Real World Applications of Computational Intelligence | TA640-643 Real World Applications of Computational Intelligence | Q334-342 Fuzzy Probabilities | TJ210.2-211.495 Fuzzy Probabilities | TA329-348 Knowledge-Based Virtual Education | TA640-643 Knowledge-Based Virtual Education | TA329-348 Computer Recognition Systems |
Fuzzy Sets -- Fuzzy Probability Theory -- Discrete Fuzzy Random Variables -- Fuzzy Queuing Theory -- Fuzzy Markov Chains -- Fuzzy Decisions Under Risk -- Continuous Fuzzy Random Variables -- Fuzzy Inventory Control -- Joint Fuzzy Probability Distributions -- Applications of Joint Distributions -- Functions of a Fuzzy Random Variable -- Functions of Fuzzy Random Variables -- Law of Large Numbers -- Sums of Fuzzy Random Variables -- Conclusions and Future Research.
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.
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