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Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach

  • Book
  • © 1998

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Authors:
  1. Bilal M. Ayyub

    1. University of Maryland, College Park, USA

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    You can also search for this author in PubMed   Google Scholar

  2. Madan M. Gupta

    1. University of Saskatchewan, Saskatoon, Canada

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: International Series in Intelligent Technologies (ISIT, volume 11)

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Table of contents (24 chapters)

  1. Front Matter

    Pages i-xxiv
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  2. Uncertainty Types, Models, and Measures

    1. The Role of Constrained Fuzzy Arithmetic in Engineering

      • George J. Klir
      Pages 1-19

    2. General Perspective on the Formalization of Uncertain Knowledge

      • Elisabeth Umkehrer, Kerstin Schill
      Pages 21-35

    3. Distributional Representations of Random Interval Measurements

      • Cliff Joslyn
      Pages 37-51

    4. A Fuzzy Morphology: a Logical Approach

      • Bernard De Baets
      Pages 53-67

  3. Applications to Engineering Systems

    1. Reliability Analysis With Fuzziness and Randomness

      • Ru-Jen Chao, Bilal M. Ayyub
      Pages 69-79

    2. Fuzzy Signal Detection With Multiple Waveform Features

      • J. R. Boston
      Pages 81-95

    3. Uncertainty Modeling of Normal Vibrations

      • Matthias Kudra
      Pages 97-107

    4. Modeling and Implementation of Fuzzy Time Point Reasoning in Microprocessor Systems

      • S. M. Yuen, K. P. Lam
      Pages 109-125

    5. Model Learning With Bayesian Networks for Target Recognition

      • Jun Liu, Kuo-Chu Chang
      Pages 127-141

    6. System Life Cycle Optimization Under Uncertainty

      • Odd Andreas Asbjornsen
      Pages 143-156

    7. Valuation-Based Systems for Pavement Management Decision Making

      • Nii O. Attoh-Okine
      Pages 157-177

  4. Fuzzy-Neuro Data Analysis and Forecasting

    1. Hybrid Least-Squares Regression Analysis

      • Yun-Hsi Oscar Chang, Bilal M. Ayyub
      Pages 179-191

    2. Linear Regression With Random Fuzzy Numbers

      • Wolfgang. Näther, Ralf. Körner
      Pages 193-212

    3. Neural Net Solutions to Systems of Fuzzy Linear Equations

      • James. J. Buckley, Thomas. Feuring, Yoichi. Hayashi
      Pages 213-232

    4. Fuzzy Logic: a Case Study in Performance Measurement

      • Salwa H. Ammar, Ronald H. Wright
      Pages 233-245

    5. Fuzzy Genetic Algorithm Based Approach to Machine Learning Under Uncertainty

      • I. Burak Özyurt, Lawrence O. Hall
      Pages 247-258

  5. Fuzzy-Neuro Systems

    1. Recurrent Neuro-Fuzzy Models of Complex Systems

      • Can IÅŸik, Mohammad Farrokhi, Jiann-Horng Lin, A. Mete Çakmakci
      Pages 259-271

    2. Adaptive Fuzzy Systems With Sinusoidal Membership Functions

      • Liang Jin, Madan M. Gupta
      Pages 273-289

  6. Fuzzy Decision Making and Optimization

    1. A Computational Method for Fuzzy Optimization

      • Weldon A. Lodwick, K. David Jamison
      Pages 291-300
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Keywords

About this book

Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

Authors and Affiliations

  • University of Maryland, College Park, USA

    Bilal M. Ayyub

  • University of Saskatchewan, Saskatoon, Canada

    Madan M. Gupta

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