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 Network Routing: Fundamentals, Applications, and Emerging Technologies
Network Routing: Fundamentals, Applications and Emerging Technologies serves as single point of reference for both advanced undergraduate and graduate students studying network routing, covering both the fundamental and more moderately advanced concepts of routing in traditional data networks such as the Internet, and emerging routing... |  |  Computational Physics: Problem Solving with Python
The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming.
This upper-division text provides an ... |  |  Applied Engineering Failure Analysis: Theory and Practice
Applied Engineering Failure Analysis: Theory and Practice provides a point of reference for engineering failure analysis (EFA) cases, presenting a compilation of case studies covering a 35-year period, from the 1970s to 2012. This period spans the era from the time when slide rules were used routinely for... |
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 Agile Model-Based Development Using UML-RSDS
This book describes the concepts and application of model-based development (MBD), model transformations, and Agile MBD to a wide range of software systems. It covers systems requirements engineering, system specification and design, verification, reuse, and system composition in the context of Agile MBD. Examples of applications in... |  |  Optimization Algorithms for Networks and Graphs
A revised and expanded advanced-undergraduate/graduate text (first ed., 1978) about optimization algorithms for problems that can be formulated on graphs and networks. This edition provides many new applications and algorithms while maintaining the classic foundations on which contemporary algorithm... |  |  Evolutionary Optimization Algorithms
A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms
Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant... |
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