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Applied Stochastic System Modeling

2012-12-06 Business & Economics
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Release : 2012-12-06
Genre : Business & Economics
Kind : eBook
Book Rating : 815/5 ( reviews)

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Book Synopsis Applied Stochastic System Modeling by : Shunji Osaki

Download or read book Applied Stochastic System Modeling written by Shunji Osaki. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: This book was written for an introductory one-semester or two-quarter course in stochastic processes and their applications. The reader is assumed to have a basic knowledge of analysis and linear algebra at an undergraduate level. Stochastic models are applied in many fields such as engineering systems, physics, biology, operations research, business, economics, psychology, and linguistics. Stochastic modeling is one of the promising kinds of modeling in applied probability theory. This book is intended to introduce basic stochastic processes: Poisson pro cesses, renewal processes, discrete-time Markov chains, continuous-time Markov chains, and Markov-renewal processes. These basic processes are introduced from the viewpoint of elementary mathematics without going into rigorous treatments. This book also introduces applied stochastic system modeling such as reliability and queueing modeling. Chapters 1 and 2 deal with probability theory, which is basic and prerequisite to the following chapters. Many important concepts of probabilities, random variables, and probability distributions are introduced. Chapter 3 develops the Poisson process, which is one of the basic and im portant stochastic processes. Chapter 4 presents the renewal process. Renewal theoretic arguments are then used to analyze applied stochastic models. Chapter 5 develops discrete-time Markov chains. Following Chapter 5, Chapter 6 deals with continuous-time Markov chains. Continuous-time Markov chains have im portant applications to queueing models as seen in Chapter 9. A one-semester course or two-quarter course consists of a brief review of Chapters 1 and 2, fol lowed in order by Chapters 3 through 6.

An Introduction to Stochastic Modeling

2014-05-10 Mathematics
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Release : 2014-05-10
Genre : Mathematics
Kind : eBook
Book Rating : 272/5 ( reviews)

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Book Synopsis An Introduction to Stochastic Modeling by : Howard M. Taylor

Download or read book An Introduction to Stochastic Modeling written by Howard M. Taylor. This book was released on 2014-05-10. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Stochastic System Reliability Modeling

1985 Reliability (Engineering)
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Release : 1985
Genre : Reliability (Engineering)
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Stochastic System Reliability Modeling by : Osaki S.

Download or read book Stochastic System Reliability Modeling written by Osaki S.. This book was released on 1985. Available in PDF, EPUB and Kindle. Book excerpt:

Stochastic System Reliability Modelling

1985-10-01 Mathematics
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Release : 1985-10-01
Genre : Mathematics
Kind : eBook
Book Rating : 198/5 ( reviews)

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Book Synopsis Stochastic System Reliability Modelling by : Shunji Osaki

Download or read book Stochastic System Reliability Modelling written by Shunji Osaki. This book was released on 1985-10-01. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to present an overview of stochastic system reliability modeling for undergraduate and graduate students, engineers and researchers. It is ideal as a one-semester undergraduate or graduate level text in reliability, applied stochastic processes, stochastic operations research and systems engineering. The topics are divided into two parts: The first part deals with probability theory and stochastic processes, which provide the basic ideas of applied stochastic processes and the second part treats their applications to system reliability modelling. Throughout the later half, Markov renewal processes are applied to formulating stochastic models for system reliability. Since a fairly intermediate level of mathematics is assumed two appendices on Laplace-Stieltjes transforms and signal flow graphs provide much background material. The text is pedagogically sound.

Basics of Applied Stochastic Processes

2009-01-24 Mathematics
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Release : 2009-01-24
Genre : Mathematics
Kind : eBook
Book Rating : 326/5 ( reviews)

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Book Synopsis Basics of Applied Stochastic Processes by : Richard Serfozo

Download or read book Basics of Applied Stochastic Processes written by Richard Serfozo. This book was released on 2009-01-24. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties of these stochastic processes. A main focus is on equilibrium distributions, strong laws of large numbers, and ordinary and functional central limit theorems for cost and performance parameters. Although these results differ for various processes, they have a common trait of being limit theorems for processes with regenerative increments. Extensive examples and exercises show how to formulate stochastic models of systems as functions of a system’s data and dynamics, and how to represent and analyze cost and performance measures. Topics include stochastic networks, spatial and space-time Poisson processes, queueing, reversible processes, simulation, Brownian approximations, and varied Markovian models. The technical level of the volume is between that of introductory texts that focus on highlights of applied stochastic processes, and advanced texts that focus on theoretical aspects of processes.

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