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Predictive analytics in system relia...

Kumar, Vijay.

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Predictive analytics in system reliability

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Predictive analytics in system reliability/ edited by Vijay Kumar, Hoang Pham.
其他作者:	Kumar, Vijay.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	xi, 282 p. :ill., digital ;24 cm.
內容註:	Chapter 1. Deep Learning Approach for the Reliability Assessment of Cloud and Edge Open Source Software (Hironobu SONE) -- Chapter 2. Parameter Estimation of Software Reliability Growth Models using Mayfly Optimization (Ankur Choudhary) -- Chapter 3. Study of Automation of Test Generation using Genetic Algorithm Approach (Sonali Vyas) -- Chapter 4. Measuring and evaluating big data factors in an enterprise using fuzzy based MOORA and Best Worst Method (Abhishek Srivastava) -- Chapter 5. Reliability assessment and profit analysis of automated teller machine system under copular repair policy (Ibrahim Yusuf) -- Chapter 6. Entropy-Based Mathematical Modeling for Software Evolution (V.B.Singh)-Chapter 7. Development of Reliability Block Diagram (RBD) Model for Reliability Analysis of a Steam Boiler System (Suyog S. Patil) -- Chapter 8. Prediction of software failure using fuzzy time series method (Mohamed Ashik. A) -- Chapter 9. Big Data Quality Management System (Yury Klochkov)-Chapter 10. A Deep Analysis of Bad Smells using Machine Learning Classifiers (Aakanshi Gupta) -- Chapter 11. Multi-Criterion Intuitionistic Fuzzy-TOPSIS Based Analysis for Software Quality Metric (Adarsh Anand)-Chapter 12. Reliability Allocation and Sensitivity Assessment of Solar Air Conditioner from Markov Process (Akshay Kumar) -- Chapter 13. Design and Development of Question Answering System using Named Entity Recognition (NER) (Abhijit Kumar) -- Chapter 14. Multi-attribute utility functions based strategic decision for software release time optimization (Vishal Pradhan) -- Chapter 15. Empirical Evaluation of Code Bad Smells in Open-Source Software using Machine learning technique (Stuti Tandon) -- Chapter 16. Reliability optimization of a system stand by system using PSO technique (Mangey Ram) -- Chapter 17. Probabilistic model for the availability analysis of the milling section of rice mill plant (Ibrahim Yusuf) -- Chapter 18. An Opportunistic Maintenance Model of Load Sharing Systems with PM and Minimal Repairs (Maryam Arabzadeh)
Contained By:	Springer Nature eBook
標題:	Decision making - Statistical methods. -
電子資源:	https://doi.org/10.1007/978-3-031-05347-4
ISBN:	9783031053474

Predictive analytics in system reliability
Predictive analytics in system reliability[electronic resource] /edited by Vijay Kumar, Hoang Pham. - Cham :Springer International Publishing :2023. - xi, 282 p. :ill., digital ;24 cm. - Springer series in reliability engineering,2196-999X. - Springer series in reliability engineering..

Chapter 1. Deep Learning Approach for the Reliability Assessment of Cloud and Edge Open Source Software (Hironobu SONE) -- Chapter 2. Parameter Estimation of Software Reliability Growth Models using Mayfly Optimization (Ankur Choudhary) -- Chapter 3. Study of Automation of Test Generation using Genetic Algorithm Approach (Sonali Vyas) -- Chapter 4. Measuring and evaluating big data factors in an enterprise using fuzzy based MOORA and Best Worst Method (Abhishek Srivastava) -- Chapter 5. Reliability assessment and profit analysis of automated teller machine system under copular repair policy (Ibrahim Yusuf) -- Chapter 6. Entropy-Based Mathematical Modeling for Software Evolution (V.B.Singh)-Chapter 7. Development of Reliability Block Diagram (RBD) Model for Reliability Analysis of a Steam Boiler System (Suyog S. Patil) -- Chapter 8. Prediction of software failure using fuzzy time series method (Mohamed Ashik. A) -- Chapter 9. Big Data Quality Management System (Yury Klochkov)-Chapter 10. A Deep Analysis of Bad Smells using Machine Learning Classifiers (Aakanshi Gupta) -- Chapter 11. Multi-Criterion Intuitionistic Fuzzy-TOPSIS Based Analysis for Software Quality Metric (Adarsh Anand)-Chapter 12. Reliability Allocation and Sensitivity Assessment of Solar Air Conditioner from Markov Process (Akshay Kumar) -- Chapter 13. Design and Development of Question Answering System using Named Entity Recognition (NER) (Abhijit Kumar) -- Chapter 14. Multi-attribute utility functions based strategic decision for software release time optimization (Vishal Pradhan) -- Chapter 15. Empirical Evaluation of Code Bad Smells in Open-Source Software using Machine learning technique (Stuti Tandon) -- Chapter 16. Reliability optimization of a system stand by system using PSO technique (Mangey Ram) -- Chapter 17. Probabilistic model for the availability analysis of the milling section of rice mill plant (Ibrahim Yusuf) -- Chapter 18. An Opportunistic Maintenance Model of Load Sharing Systems with PM and Minimal Repairs (Maryam Arabzadeh)

This book provides engineers and researchers knowledge to help them in system reliability analysis using machine learning, artificial intelligence, big data, genetic algorithm, information theory, multi-criteria decision making, and other techniques. It will also be useful to students learning reliability engineering. The book brings readers up to date with how system reliability relates to the latest techniques of AI, big data, genetic algorithm, information theory, and multi-criteria decision making and points toward future developments in the subject.

ISBN: 9783031053474

Standard No.: 10.1007/978-3-031-05347-4doiSubjects--Topical Terms:

750247
Decision making
--Statistical methods.

LC Class. No.: HD3023

Dewey Class. No.: 620.00452

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520 $a This book provides engineers and researchers knowledge to help them in system reliability analysis using machine learning, artificial intelligence, big data, genetic algorithm, information theory, multi-criteria decision making, and other techniques. It will also be useful to students learning reliability engineering. The book brings readers up to date with how system reliability relates to the latest techniques of AI, big data, genetic algorithm, information theory, and multi-criteria decision making and points toward future developments in the subject.
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