
Nature-Inspired Computing Paradigms in Systems
Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM)
- 1st Edition - June 18, 2021
- Imprint: Academic Press
- Editors: Mohamed Arezki Mellal, Michael G. Pecht
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 3 7 4 9 - 6
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 3 7 5 0 - 2
Nature-Inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM) covers several a… Read more

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Request a sales quoteNature-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
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Editor biographies
- Preface
- Acknowledgment
- Chapter 1: Reliability optimization of power plant safety system using grey wolf optimizer and shuffled frog-leaping algorithm
- Abstract
- 1: Introduction
- 2: Literature review
- 3: Problem description
- 4: Grey wolf optimizer
- 5: Shuffled frog-leaping algorithm
- 6: Results and discussion
- 7: Conclusions
- Chapter 2: Design optimization of a car side safety system by particle swarm optimization and grey wolf optimizer
- Abstract
- 1: Introduction
- 2: Design optimization of a car side safety system
- 3: Particle swarm optimization
- 4: Grey wolf optimizer
- 5: Results and discussion
- 6: Conclusions
- Chapter 3: Genetic algorithms: Principles and application in RAMS
- Abstract
- 1: Introduction
- 2: GA construction
- 3: Stop condition
- 4: GA applications
- 5: Industry 4.0 and optimization
- 6: Advantages and disadvantages of the GA
- 7: Conclusion
- Chapter 4: Evolutionary optimization for resilience-based planning for power distribution networks
- Abstract
- 1: Introduction
- 2: Problem description and formulation
- 3: Solution methodology
- 4: Results
- 5: Conclusions
- Chapter 5: Application of nature-inspired computing paradigms in optimal design of structural engineering problems—a review
- Abstract
- 1: Introduction
- 2: Nature-inspired algorithms
- 3: Nature-inspired metaheuristics in optimal design of structural engineering problems
- 4: Discussion
- 5: Conclusions
- Chapter 6: A data-driven model for fire safety strategies assessment using artificial neural networks and genetic algorithms
- Abstract
- Acknowledgments
- 1: Introduction
- 2: Methodology
- 3: Results and discussions
- 4: Conclusions
- Chapter 7: Application of artificial neural networks in polymer electrolyte membrane fuel cell system prognostics
- Abstract
- 1: Introduction
- 2: Description of fuel cell test bench and experimental data
- 3: A hybrid approach for PEMFC prognosis
- 4: Effectiveness of proposed hybrid approach in PEMFC predictions
- 5: Input parameter optimization using correlation-based analysis
- 6: Conclusion
- Chapter 8: Reliability redundancy allocation problems under fuzziness using genetic algorithm and dual-connection numbers
- Abstract
- 1: Introduction
- 2: Prerequisite mathematics
- 3: Problem formulation: Reliability redundancy allocation problem (RRAP)
- 4: Solution procedure: Genetic algorithm-based constrained handling approach
- 5: Numerical example
- 6: Concluding remarks
- Index
- Edition: 1
- Published: June 18, 2021
- Imprint: Academic Press
- No. of pages: 144
- Language: English
- Paperback ISBN: 9780128237496
- eBook ISBN: 9780128237502
MM
Mohamed Arezki Mellal
MP