Robust Engineering Experiment Design: Theory and Practice

Hari Mohan Pandey

ISBN 10: 3659841064 / ISBN 13: 9783659841064

Verlag: Scholars' Press Aug 2016, 2016

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a comprehensive hands-on guide to develop an experiment, which should show a statistically sound behavior. During writing this book the author has assumed that you've no idea about developing a robust scientific experiment of a standard. The researchers familiar with the robust design can also utilize this book as a single source of information on achieving the goal of robust and statistically verified design. The rationale behind preparing the content of this type is outlined ahead: Researchers and practitioners frequently spend most of their time in fine-tuning of an algorithm then designing and implementing them. This is very true when developing heuristics and meta-heuristics employed for optimization problem and many times in software development, where the correct choice of values for search parameters has a considerable effect on the performance of the procedure. Determining the optimal parameters is a continuous engineering task, which goals are to reduce the production costs and to achieve the desired product quality. This is because you can only change the controllable factors in the process. 100 pp. Englisch.

Bestandsnummer des Verkäufers 9783659841064

Bibliografische Details

• Titel: Robust Engineering Experiment Design: Theory and Practice
• Verlag: Scholars' Press Aug 2016
• Erscheinungsjahr: 2016
• Sprache: Englisch
• ISBN-10: 3659841064
• ISBN-13: 9783659841064
• Einband: Taschenbuch
• Zustand: Neu

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Inhaltsangabe

This book is a comprehensive hands-on guide to develop an experiment, which should show a statistically sound behavior. During writing this book the author has assumed that you’ve no idea about developing a robust scientific experiment of a standard. The researchers familiar with the robust design can also utilize this book as a single source of information on achieving the goal of robust and statistically verified design. The rationale behind preparing the content of this type is outlined ahead: Researchers and practitioners frequently spend most of their time in fine-tuning of an algorithm then designing and implementing them. This is very true when developing heuristics and meta-heuristics employed for optimization problem and many times in software development, where the correct choice of values for search parameters has a considerable effect on the performance of the procedure. Determining the optimal parameters is a continuous engineering task, which goals are to reduce the production costs and to achieve the desired product quality. This is because you can only change the controllable factors in the process.