Reliability Analysis and Modeling for Complex Systems is a crucial resource for engineers and technologists grappling with modern challenges. As technology advances and safety concerns mount, the complexity of systems like autonomous vehicles and critical infrastructure demands innovative reliability assessment methods. This book bridges theory and practice, offering practical solutions for professionals navigating the intricate world of reliability engineering. Through real-world case studies and interdisciplinary insights, it equips readers to address the multifaceted challenges of ensuring dependability in today's interconnected technological landscape.
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1. The Rationale behind Reliability Analysis in Complex Systems: Issues, Challenges, and the Imperative of Addressing Human Factors
2. A Reliability Modelling and Exploratory Data Analysis Approach to Understanding Complex Human Well-Being Systems: Decoding the Interplay of Financial Prosperity and Life Satisfaction
3. Deep Learning augmented Human Detection and Reliable Assessment for Search and Rescue in Disasters
4. Exploratory Human Factors Analysis for Reliable Happiness Perception in Complex Social Media Systems
5. Human Factors and Reliability in Complex Systems
6. Human Factors design considerations for complex systems
7. Impact of Smart Healthcare Devices in daily life
8. LEVERAGING AI TO ENHANCE HUMAN FACTOR ANALYSIS IN COMPLEX SYSTEM RELIABILITY
9. Digitalization of Healthcare: The Rise of Digital Twin Trend Worldwide and Its Implementation in Healthcare
10. Reliability Analysis in Healthcare Systems Addressing Technical and Human Factors
11. Reliability in Healthcare Systems
12. Reliability in Healthcare Systems ensuring patient safety
13. The Role of Diet and Nutrition in Alzheimer's Disease: Exploring the Gut-Cognitive Health Connection
14. Optimizing Parkinson's Disease Detection Based on Machine Learning and Statistical Feature Selection Approach
15. Reliability Measures in Wireless Zigbee Network Communication Systems: Addressing Data Loss and Remote Signal Strength
16. Solar Power Prediction using Computer Vision and Machine Intelligence: Predicting and Optimizing Solar Energy Generation
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Equips professionals with practical solutions to navigate the challenges of ensuring dependability in modern technology
Dives deeply into advanced probabilistic modeling and analysis techniques tailored for complex systems. This content addresses the needs of reliability engineers and researchers who seek to apply cutting-edge methods to their projects
Includes interdisciplinary perspectives, such as human factors and cyber-physical systems, which is essential for addressing the real-world challenges the target audience faces. This approach will help readers tackle complex system reliability from multiple angles
Real-world case studies that bridge theory and practice, helping practitioners and academics understand how to apply reliability analysis to complex systems in various domains
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Produktdetaljer
ISBN
9780443336553
Publisert
2025-11-07
Utgiver
Elsevier - Health Sciences Division
Vekt
450 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
384