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Applied Research in Uncertainty Modeling and Analysis

  • Book
  • © 2005

Overview

Editors:
  1. Nii O. Attoh-Okine

    1. University of Delaware, Newark, USA

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  2. Bilal M. Ayyub

    1. University of Maryland, College Park, USA

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    You can also search for this editor in PubMed   Google Scholar

  • Provides broad coverage of uncertainty analysis/modeling and its application
  • Presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise
  • Focusing explicitly on theory, this work uses real-world examples to demonstrate the strength of the chosen methodology

Part of the book series: International Series in Intelligent Technologies (ISIT, volume 20)

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Table of contents (23 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Philosophical and Theoretical Bases for Analyzing and Modeling Uncertainty and Ignorance

    • Bilal M. Ayyub
    Pages 1-18

  3. A Self-Organizing Neural Network by Dynamic and Spatial Changing Weights

    • Noriyasu Homma, Madan M. Gupta, Masao Sakai, Makoto Yoshizawa, Kenichi Abe
    Pages 19-30

  4. Simulation of Fuzzy Systems I

    • James J. Buckley, Kevin D. Reilly, Xidong Zheng
    Pages 31-60

  5. Simulation Of Fuzzy Systems II

    • James J. Buckley, Kevin D. Reilly, Xidong Zheng
    Pages 61-90

  6. Event-Related Potential Noise Reduction Using the Hidden Markov Tree Model

    • Rafael E. Herrera, Mingui Sun, Ronald E. Dahl, Neal D. Ryan, Robert J. Sclabassi
    Pages 91-113

  7. Change Detection in Image Sequence Based on Markov Random Field and Mean Field Theory

    • Qiang Liu, Mingui Sun, Ching-Chung Li, Robert J. Sclabassi
    Pages 115-137

  8. Analysis of Multi-Channel Subdural EEG by Recurrent Neural Networks

    • Robyn R. Bates, Mingui Sun, Mark L. Scheuer, Robert J. Sclabassi
    Pages 139-159

  9. Multicriteria Optimization Under Parametric Uncertainty

    • Luke E. K. Achenie, G. M. Ostrovsky
    Pages 161-191

  10. Design of Neural Networks for Pavement Rutting

    • Rafiqul Alam Tarefder, Musharraf Zaman
    Pages 193-213

  11. Neural Networks for Residential Infrastructure Management

    • Deidre E. Paris
    Pages 215-248

  12. Evacuation Simulation in Underground Mall by Artificial Life Technology

    • Hitoshi Furuta, Masahiro Yasui
    Pages 249-265

  13. Epistemic Uncertainty and the Management of High Risk Exposures

    • Mark Jablonowski
    Pages 267-281

  14. Experiment with a Hierarchical Text Categorization Method on WIPO Patent Collections

    • Domonkos Tikk, György Biró, Jae Dong Yang
    Pages 283-302

  15. Study of Transportation and Uncertainty

    • Shinya Kikuchi
    Pages 303-319

  16. Multi Agent Systems Approach to Parking Facilities Management

    • Mauro Dell’Orco, DuÅ¡an Teodorović
    Pages 321-339

  17. Modeling Transportation Choice Through Utility-Based Multi-Layer Feedforward Networks

    • Giulio Erberto Cantarella, Stefano de Luca
    Pages 341-368

  18. Heterogeneity in Commuter Departure Time Decision: a Prospect Theoretic Approach

    • Metin Senbil, Ryuichi Kitamura
    Pages 369-398

  19. Importance of Fuzzy Sets Definitions for Fuzzy Signal Controllers

    • Maria Alice P. Jacques, Daliana B. L. M. Santos, Matti Pursula, Iisakki Kosonen
    Pages 399-416

  20. Reliability Evaluation of Realistic Structures Using FEM

    • Jungwon Huh, Achintya Haldar, Seung Y. Lee
    Pages 417-442
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Keywords

About this book

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.

Reviews

From the reviews of the first edition:

"This book presents a collection of interesting articles in the general framework of uncertainty modeling and analysis. The tools used come from various disciplines including statistics and operations research. … an operations research instructor may consider Applied Research in Uncertainty Modeling and Analysis favorably as a good source book … ." (Sailes K. Sengupta, Technometrics, Vol. 48 (4), 2006)

Editors and Affiliations

  • University of Delaware, Newark, USA

    Nii O. Attoh-Okine

  • University of Maryland, College Park, USA

    Bilal M. Ayyub

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