Nature-inspired computing paradigms in systems : reliability, availability, maintainability, safety and cost (RAMS+C) and prognostics and health management

Nature-inspired computing paradigms in systems : reliability, availability, maintainability, safety and cost (RAMS+C) and prognostics and health management (PHM) – Ebook Instant Download/Delivery ISBN(s): 9780128237502,0128237503

 

Product detail:

• ISBN 10: 0128237503
• ISBN 13: 9780128237502
• Author: Academic Press

Nature-Inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM) covers several areas that include bioinspired techniques and optimization approaches for system dependability.

The book addresses the issue of integration and interaction of the bioinspired techniques in system dependability computing so that intelligent decisions, design, and architectures can be supported. It brings together these emerging areas under the umbrella of bio- and nature-inspired computational intelligence.

The primary audience of this book includes experts and developers who want to deepen their understanding of bioinspired computing in basic theory, algorithms, and applications. The book is also intended to be used as a textbook for masters and doctoral students who want to enhance their knowledge and understanding of the role of bioinspired techniques in system dependability.

• Provides the latest review
• Covers various nature-inspired techniques applied to RAMS+C and PHM problems
• Includes techniques applied to new applications

Table of contents:

1. Chapter 1: Reliability optimization of power plant safety system using grey wolf optimizer and shuffled frog-leaping algorithm
2. Chapter 2: Design optimization of a car side safety system by particle swarm optimization and grey wolf optimizer
3. Chapter 3: Genetic algorithms: Principles and application in RAMS
4. Chapter 4: Evolutionary optimization for resilience-based planning for power distribution networks
5. Chapter 5: Application of nature-inspired computing paradigms in optimal design of structural engineering problems—a review
6. Chapter 6: A data-driven model for fire safety strategies assessment using artificial neural networks and genetic algorithms
7. Chapter 7: Application of artificial neural networks in polymer electrolyte membrane fuel cell system prognostics
8. Chapter 8: Reliability redundancy allocation problems under fuzziness using genetic algorithm and dual-connection numbers

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