投票 发表于 2025-3-23 10:26:31

0884-8289 pplications 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..978-1-4419-3986-9978-0-387-29337-0Series ISSN 0884-8289 Series E-ISSN 2214-7934

Project 发表于 2025-3-23 15:51:49

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使饥饿 发表于 2025-3-23 21:09:28

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发表于 2025-3-24 01:05:42

Wai-Ki Ching,Michael K. NgMarkov chains are a powerful and widely used tool for analyzing a variety of stochastic systems over time.Systematically discusses all the models beginning with the basic to the more advanced and illu

不容置疑 发表于 2025-3-24 05:27:45

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Endemic 发表于 2025-3-24 06:58:30

Higher-order Markov Chains,In this chapter, a higher-order Markov chain model is proposed with estimation methods for the model parameters. The higher-order Markov chain model is then applied to a number of applications such as DNA sequences, sales demand predictions and web page predictions, Newsboy’s problem. Further extension of the model is also discussed.

过份 发表于 2025-3-24 11:02:58

https://doi.org/10.1007/0-387-29337-XAlgorithms; Business and management applications; Markov chain; Markov chains; Markov decision process; M

Carbon-Monoxide 发表于 2025-3-24 18:23:12

Re-manufacturing Systems,state probability distributions of the models are either obtained in closed form or can be solved by fast numerical algorithms. The models here concern only single-item, it will be interesting to extend the results to multi-item case.

使迷惑 发表于 2025-3-24 23:02:50

Hidden Markov Model for Customers Classification,ntly. Application to customers classification with practical data taken from a computer service company is presented and analyzed. Further disussions on new HMMs and applications will be given in Chapter 8.

NORM 发表于 2025-3-25 00:20:49

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查看完整版本: Titlebook: Markov Chains: Models, Algorithms and Applications; Wai-Ki Ching,Michael K. Ng Book 20061st edition Springer-Verlag US 2006 Algorithms.Bus