Non-Fiction Books:

Network Reliability

A Lecture Course
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Description

This introductory book equips the reader to apply the core concepts and methods of network reliability analysis to real-life problems. It explains the modeling and critical analysis of systems and probabilistic networks, and requires only a minimal background in probability theory and computer programming. Based on the lecture notes of eight courses taught by the authors, the book is also self-contained, with no theory needed beyond the lectures. The primary focus is on essential “modus operandi,” which are illustrated in numerous examples and presented separately from the more difficult theoretical material.

Author Biography:

Ilya B. Gertsbakh is Professor Emeritus in the Department of Mathematics at Ben-Gurion University of the Negev, Israel. He is author or coauthor of seven books, the recent of which is “Ternary networks: Reliability and Monte Carlo” (with Yoseph Shpungin and Radislav Vaisman), published by Springer in 2014. Ilya Gertsbakh has published some 100 papers on topics in operations research, reliability, applied probability and applied statistics. He received M.Sc degrees in mechanical engineering and mathematics (1961) from Latvian State University in Riga, Latvia, and the Ph.D. degree (1964) in applied probability and statistics from Latvian Academy of Sciences, also in Riga.    Yoseph Shpungin is Professor Emeritus in the Software Engineering Department, at Shamoon College of Engineering, Beer Sheva, Israel. He is a coauthor of three books and numerous publications in international scientific journals. He received his M.Sc degree in mathematics(1969) from Latvian State University in Riga, Latvia, and Ph.D. degree (1997) in mathematics from Ben Gurion University, Beer Sheva, Israel. 
Release date NZ
January 2nd, 2020
Audience
  • Professional & Vocational
Edition
1st ed. 2020
Illustrations
27 Illustrations, color; 21 Illustrations, black and white; IX, 90 p. 48 illus., 27 illus. in color.
Pages
90
ISBN-13
9789811514579
Product ID
31779592

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