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Applied Research In Uncertainty Modeling And Analysis Nii O Attohokine Bilal M Ayyub

  • SKU: BELL-4097286
Applied Research In Uncertainty Modeling And Analysis Nii O Attohokine Bilal M Ayyub
$ 31.00 $ 45.00 (-31%)

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Applied Research In Uncertainty Modeling And Analysis Nii O Attohokine Bilal M Ayyub instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 21.23 MB
Pages: 562
Author: Nii O Attoh-Okine; Bilal M Ayyub
ISBN: 9780387235356, 9780387235509, 0387235353, 0387235507
Language: English
Year: 2005

Product desciption

Applied Research In Uncertainty Modeling And Analysis Nii O Attohokine Bilal M Ayyub by Nii O Attoh-okine; Bilal M Ayyub 9780387235356, 9780387235509, 0387235353, 0387235507 instant download after payment.

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.

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