Nature-Inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM) 1st Edition by Mohamed Arezki Mellal, Michael G. Pecht 9780128237502 0128237503

Nature-Inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM) 1st Edition Mohamed Arezki Mellal And Michael G. Pecht – Ebook Instant Download/Delivery ISBN(s): 9780128237502, 0128237503

Product details:

• ISBN 10: 0128237503
• ISBN 13: 9780128237502
• Author: Mohamed Arezki Mellal, Michael G. Pecht 

Nature-Inspired Computing Paradigms in Systems
Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM)

Table contents:

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

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