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Towards Efficient Fuzzy Information Processing

Using the Principle of Information Diffusion

  • Book
  • © 2002

Overview

Authors:
  1. Chongfu Huang

    1. Institute of Resources Science, Beijing Normal University, Beijing, China

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    You can also search for this author in PubMed   Google Scholar

  2. Yong Shi

    1. College of Information Science and Technology, University of Nebraska at Omaha, Omaha, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Book on fuzzy concepts to explain the dynamics and limitation of kernel functions
  • Gives diffusion models for practical problems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 99)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xxi
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  2. Principle of Information Diffusion

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • Chongfu Huang, Yong Shi
      Pages 3-21

    3. Information Matrix

      • Chongfu Huang, Yong Shi
      Pages 23-54

    4. Some Concepts From Probability and Statistics

      • Chongfu Huang, Yong Shi
      Pages 55-80

    5. Information Distribution

      • Chongfu Huang, Yong Shi
      Pages 81-127

    6. Information Diffusion

      • Chongfu Huang, Yong Shi
      Pages 129-168

    7. Quadratic Diffusion

      • Chongfu Huang, Yong Shi
      Pages 169-189

    8. Normal Diffusion

      • Chongfu Huang, Yong Shi
      Pages 191-212

  3. Applications

    1. Front Matter

      Pages 213-213
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    2. Estimation of Epicentral Intensity

      • Chongfu Huang, Yong Shi
      Pages 215-246

    3. Estimation of Isoseismal Area

      • Chongfu Huang, Yong Shi
      Pages 247-271

    4. Fuzzy Risk Analysis

      • Chongfu Huang, Yong Shi
      Pages 273-295

    5. System Analytic Model for Natural Disasters

      • Chongfu Huang, Yong Shi
      Pages 297-324

    6. Fuzzy Risk Calculation

      • Chongfu Huang, Yong Shi
      Pages 325-363

  4. Back Matter

    Pages 365-370
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Keywords

About this book

When we learn from books or daily experience, we make associations and draw inferences on the basis of information that is insufficient for under­ standing. One example of insufficient information may be a small sample derived from observing experiments. With this perspective, the need for de­ veloping a better understanding of the behavior of a small sample presents a problem that is far beyond purely academic importance. During the past 15 years considerable progress has been achieved in the study of this issue in China. One distinguished result is the principle of in­ formation diffusion. According to this principle, it is possible to partly fill gaps caused by incomplete information by changing crisp observations into fuzzy sets so that one can improve the recognition of relationships between input and output. The principle of information diffusion has been proven suc­ cessful for the estimation of a probability density function. Many successful applications reflect the advantages of this new approach. It also supports an argument that fuzzy set theory can be used not only in "soft" science where some subjective adjustment is necessary, but also in "hard" science where all data are recorded.

Authors and Affiliations

  • Institute of Resources Science, Beijing Normal University, Beijing, China

    Chongfu Huang

  • College of Information Science and Technology, University of Nebraska at Omaha, Omaha, USA

    Yong Shi

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