Name: applied research in uncertainty modeling and analysis (en Inglés)
SKU: 25620771
Price: 149.83 USD
Availability: InStock
Author: Ayyub, Bilal M.

portada applied research in uncertainty modeling and analysis (en Inglés)

applied research in uncertainty modeling and analysis (en Inglés)

Formato

Libro Físico

Ilustrado por

Bilal M. Ayyub

Editorial

Springer

Autor

Ayyub, Bilal M.

Año

2010

Idioma

Inglés

N° páginas

545

Encuadernación

Tapa Blanda

Dimensiones

23.4x15.6x2.9 cm

Peso

0.78 kg.

ISBN

1441936351

ISBN13

9781441936356

Categorías

Teoría y filosofía económicas
Investigación operativa
Ingeniería: general

applied research in uncertainty modeling and analysis (en Inglés)

Bilal M. Ayyub (Ilustrado por) · Springer · Tapa Blanda

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Reseña del libro "applied research in uncertainty modeling and analysis (en Inglés)"

The application areas of uncertainty are numerous and diverse, including all fields of engineering, computer science, systems control and finance. Determining appropriate ways and methods of dealing with uncertainty has been a constant challenge. The theme for this book is better understanding and the application of uncertainty theories. This book, with invited chapters, deals with the uncertainty phenomena in diverse fields. The book is an outgrowth of the Fourth International Symposium on Uncertainty Modeling and Analysis (ISUMA), which was held at the center of Adult Education, College Park, Maryland, in September 2003. All of the chapters have been carefully edited, following a review process in which the editorial committee scrutinized each chapter. The contents of the book are reported in twenty-three chapters, covering more than . . ... pages. This book is divided into six main sections. Part I (Chapters 1-4) presents the philosophical and theoretical foundation of uncertainty, new computational directions in neural networks, and some theoretical foundation of fuzzy systems. Part I1 (Chapters 5-8) reports on biomedical and chemical engineering applications. The sections looks at noise reduction techniques using hidden Markov models, evaluation of biomedical signals using neural networks, and changes in medical image detection using Markov Random Field and Mean Field theory. One of the chapters reports on optimization in chemical engineering processes.