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.
General
Imprint: |
Springer-Verlag
|
Country of origin: |
Germany |
Series: |
Studies in Fuzziness and Soft Computing, 115 |
Release date: |
June 2012 |
First published: |
2003 |
Authors: |
James J Buckley
|
Dimensions: |
235 x 155 x 10mm (L x W x T) |
Format: |
Paperback
|
Pages: |
165 |
Edition: |
Softcover reprint of the original 1st ed. 2003 |
ISBN-13: |
978-3-642-86788-0 |
Categories: |
Books >
Computing & IT >
Applications of computing >
Artificial intelligence >
General
|
LSN: |
3-642-86788-X |
Barcode: |
9783642867880 |
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