Reliability Engineering and Computational Intelligence
- Length: 315 pages
- Edition: 1
- Language: English
- Publisher: Springer
- Publication Date: 2021-08-08
- ISBN-10: 3030745554
- ISBN-13: 9783030745554
- Sales Rank: #0 (See Top 100 Books)
Computational intelligence is rapidly becoming an essential part of reliability engineering. This book offers a wide spectrum of viewpoints on the merger of technologies. Leading scientists share their insights and progress on reliability engineering techniques, suitable mathematical methods, and practical applications. Thought-provoking ideas are embedded in a solid scientific basis that contribute to the development the emerging field.
This book is for anyone working on the most fundamental paradigm-shift in resilience engineering in decades. Scientists benefit from this book by gaining insight in the latest in the merger of reliability engineering and computational intelligence. Businesses and (IT) suppliers can find inspiration for the future, and reliability engineers can use the book to move closer to the cutting edge of technology.
Cover Front Matter Mathematical and Computational Intelligence Methods in Reliability Engineering System Reliability Analysis and Assessment by Means of Logic Differential Calculus and Hasse Diagram The Survival Signature for Quantifying System Reliability: An Introductory Overview from Practical Perspective Application of Fuzzy Decision Tree for the Construction of Structure Function for System Reliability Analysis Based on Uncertain Data Unavailability Optimization of a System Undergoing a Real Ageing Process Under Failure Based PM Minimal Filtering Algorithms for Convolutional Neural Networks Digital Technologies in Reliability Engineering New Challenges and Opportunities in Reliability Engineering of Complex Technical Systems Development of Structured Arguments for Assurance Case Making Reliability Engineering and Computational Intelligence Solutions SMARTER Method for Determining the Structural Reliability of a Network Based on a Hyperconverged Architecture Database Approach for Increasing Reliability in Distributed Information Systems Time Dependent Reliability Analysis of the Data Storage System Based on the Structure Function and Logic Differential Calculus Energy Efficiency for IoT Image Analysis and Other Applications of Computational Intelligence in Reliability Engineering Knowledge-Based Multispectral Remote Sensing Imagery Superresolution Neural Network Training Acceleration by Weight Standardization in Segmentation of Electronic Commerce Images Waterproofing Membranes Reliability Analysis by Embedded and High-Throughput Deep-Learning Algorithm Network of Autonomous Units for the Complex Technological Objects Reliable Monitoring A Correlative Method to Rank Sensors with Information Reliability: Interval-Valued Numbers Case COVID-19 Pandemic Risk Analytics: Data Mining with Reliability Engineering Methods for Analyzing Spreading Behavior and Comparison with Infectious Diseases
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