Markov Chains
Models, Algorithms and Applications (International Series in Operations Research & Management Science)
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Word Count
52,000 words, Guess
Page Count
208 pages
Identifiers
- Open LibraryOL7445168M
- ISBN-139780387293356
- ISBN-100387293353
- OCLC Control Number62866364
- OCLC Control Numbermarkovchainsmode00chin_193
and 3 more
- Library of Congress Control Number2005933263
- LibraryThing4562848
- Goodreads7332837
Classifications
- LCCQA274.7 .C47 2006
Description
Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.
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