Книга Statistical Reliability Engineering: Methods, Models and Applications

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Язык книги
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This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field.

The book covers a wide range of methods and models in reliability, and their applications, including:

  • statistical methods and model selection for machine learning; 
  • models for maintenance and software reliability; 
  • statistical reliability estimation of complex systems; and
  • statistical reliability analysis of k out of n systems, standby systems and repairable systems.

Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.

Код товара
20614805
Характеристики
Автор
Тип обложки
Мягкий
Язык
Английский
Описание книги

This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field.

The book covers a wide range of methods and models in reliability, and their applications, including:

  • statistical methods and model selection for machine learning; 
  • models for maintenance and software reliability; 
  • statistical reliability estimation of complex systems; and
  • statistical reliability analysis of k out of n systems, standby systems and repairable systems.

Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.

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