Markov Chains: Models, Algorithms and Applications

Wai-Ki Ching

ISBN 10: 1441939865 / ISBN 13: 9781441939869

Published by Berlin Springer US Springer Nov 2010, 2010

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 208 pp. Englisch.

Seller Inventory # 9781441939869

Bibliographic Details

• Title: Markov Chains: Models, Algorithms and Applications
• Publisher: Berlin Springer US Springer Nov 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 1441939865
• ISBN 13: 9781441939869
• Binding: Taschenbuch
• Condition: Neu

About this title

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.

About the Author

Michael K. Ng is an Associate Professor in the Department of Mathematics and also Adjunct Research Fellow in the E-Business Technology Institute at The University of Hong Kong.