Description: Markov Chains: Models, Algorithms and Applications Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Wai-Ki Ching, Michael K. Ng Format: Paperback Publisher: Springer-Verlag New York Inc., United States Imprint: Springer-Verlag New York Inc. ISBN-13: 9781441939869, 978-1441939869 Synopsis 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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Book Title: Markov Chains: Models, Algorithms and Applications
Number of Pages: 208 Pages
Publication Name: Markov Chains: Models, Algorithms and Applications
Language: English
Publisher: Springer-Verlag New York Inc.
Item Height: 235 mm
Subject: Engineering & Technology, Computer Science, Mathematics, Management
Publication Year: 2010
Type: Textbook
Item Weight: 349 g
Subject Area: Data Analysis
Author: Wai-Ki Ching, Michael K. Ng
Item Width: 155 mm
Series: International Series in Operations Research & Management Science
Format: Paperback
