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Early Software Reliability Prediction
The development of software system with acceptable level of reliability and quality within available time frame and budget becomes a challenging objective. This objective could be achieved to some extent through early prediction of number of faults present in the software, which reduces the cost of development as it provides an opportunity to make early corrections during development process. The book presents an early software reliability prediction model that will help to grow the reliability of the software systems by monitoring it in each development phase, i.e. from requirement phase to testing phase. Different approaches are discussed in this book to tackle this challenging issue. An i...
Soft Computing: Theories and Applications
This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing, and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2021), organized online. The book offers valuable insights into soft computing for teachers and researchers alike; the book will inspire further research in this dynamic field.
Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science. The book Discusses basic as well as advance research in the field of prognostics. Explores integration of data collection, fault detection, degradation modeling and reliability prediction in one volume. Covers prognostics and health management (PHM) of engineering systems. Discusses latest approaches in the field of prognostics based on machine learning. The text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science.
Interconnection Network Reliability Evaluation
This book presents novel and efficient tools, techniques and approaches for reliability evaluation, reliability analysis, and design of reliable communication networks using graph theoretic concepts. In recent years, human beings have become largely dependent on communication networks, such as computer communication networks, telecommunication networks, mobile switching networks etc., for their day-to-day activities. In today's world, humans and critical machines depend on these communication networks to work properly. Failure of these communication networks can result in situations where people may find themselves isolated, helpless and exposed to hazards. It is a fact that every component ...
Comprehensive Textbook of Clinical Radiology Volume VI: Musculoskeletal System - eBook
Comprehensive Textbook of Clinical Radiology Volume VI: Musculoskeletal System - eBook
Artificial Neural Network Applications for Software Reliability Prediction
This book provides a starting point for software professionals to apply artificial neural networks for software reliability prediction without having analyst capability and expertise in various ANN architectures and their optimization. Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process are presented. Applications of artificial neural network for the above purposes are discussed with experimental results in this book so that practitioners can easily use ANN models for predicting software reliability indicators.
Soft Computing: Theories and Applications
The book focuses on soft computing and its applications to solve real-world problems occurring in different domains ranging from medicine and healthcare, and supply chain management to image processing and cryptanalysis. It includes high-quality papers presented in the International Conference on Soft Computing: Theories and Applications (SoCTA 2017), organized by Bundelkhand University, Jhansi, India. Offering significant insights into soft computing for teachers and researchers alike, the book inspires more researchers to work in the field of soft computing.
Modern Manufacturing Systems
This new volume explores recent research on advanced technologies and methods in production engineering, emphasizing effective overall process control and enhanced optimization. The authors include real-life case studies on advanced machining methods, traditional manufacturing technologies, advanced composite materials, processing with hybrid manufacturing techniques, various joining processes and their applications, micro-structure analysis, and more.
