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Published by John Wiley & Sons Inc, New York, 2017
ISBN 10: 1119223547 ISBN 13: 9781119223542
Language: English
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Hardcover. Condition: new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Add to basketGebunden. Condition: New. Manjubala Bisi is currently an Assistant Professor in the Computer Science and Engineering Department, Kakatiya Institute of Technology and Science, Warangal, Telengana, India. She received her PhD from the Indian Institute of Technology Kharagpur in Reliab.
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ISBN 10: 1119223547 ISBN 13: 9781119223542
Language: English
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Published by John Wiley & Sons 2016-08-04, 2016
ISBN 10: 1119223547 ISBN 13: 9781119223542
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ISBN 10: 1119223547 ISBN 13: 9781119223542
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Add to basketHardcover. Condition: new. Hardcover. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Add to basketBuch. Condition: Neu. Neuware - 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 is presented as well. 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.
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Add to basketHardcover. Condition: Brand New. 250 pages. 9.25x6.25x1.00 inches. In Stock.
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ISBN 10: 1119223547 ISBN 13: 9781119223542
Language: English
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Add to basketCondition: New. Series: Performability Engineering Series. Num Pages: 250 pages. BIC Classification: TJ; UMZ; UYQN. Category: (P) Professional & Vocational. Weight in Grams: 666. . 2017. 1st Edition. Hardcover. . . . .
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ISBN 10: 1119223547 ISBN 13: 9781119223542
Language: English
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Add to basketHardcover. Condition: new. Hardcover. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by John Wiley & Sons Inc, 2017
ISBN 10: 1119223547 ISBN 13: 9781119223542
Language: English
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Condition: New. Series: Performability Engineering Series. Num Pages: 250 pages. BIC Classification: TJ; UMZ; UYQN. Category: (P) Professional & Vocational. Weight in Grams: 666. . 2017. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
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Add to basketHardcover. Condition: Brand New. 250 pages. 9.25x6.25x1.00 inches. In Stock. This item is printed on demand.