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Backward Fuzzy Rule Interpolation

  • Shangzhu Jin
  • Qiang Shen
  • Jun Peng
Book

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Shangzhu Jin, Qiang Shen, Jun Peng
    Pages 1-15
  3. Shangzhu Jin, Qiang Shen, Jun Peng
    Pages 17-57
  4. Shangzhu Jin, Qiang Shen, Jun Peng
    Pages 91-106
  5. Shangzhu Jin, Qiang Shen, Jun Peng
    Pages 107-119
  6. Shangzhu Jin, Qiang Shen, Jun Peng
    Pages 121-141
  7. Shangzhu Jin, Qiang Shen, Jun Peng
    Pages 143-151
  8. Back Matter
    Pages 153-159

About this book

Introduction

This book chiefly presents a novel approach referred to as backward fuzzy rule interpolation and extrapolation (BFRI). BFRI allows observations that directly relate to the conclusion to be inferred or interpolated from other antecedents and conclusions. Based on the scale and move transformation interpolation, this approach supports both interpolation and extrapolation, which involve multiple hierarchical intertwined fuzzy rules, each with multiple antecedents. As such, it offers a means of broadening the applications of fuzzy rule interpolation and fuzzy inference. The book deals with the general situation, in which there may be more than one antecedent value missing for a given problem. Two techniques, termed the parametric approach and feedback approach, are proposed in an attempt to perform backward interpolation with multiple missing antecedent values. In addition, to further enhance the versatility and potential of BFRI, the backward fuzzy interpolation method is extended to support α-cut based interpolation by employing a fuzzy interpolation mechanism for multi-dimensional input spaces (IMUL). Finally, from an integrated application analysis perspective, experimental studies based upon a real-world scenario of terrorism risk assessment are provided in order to demonstrate the potential and efficacy of the hierarchical fuzzy rule interpolation methodology.


Keywords

Artificial Intelligence Approximation Reasoning Fuzzy Logic Fuzzy Interpolation Backward Fuzzy Interpoltion

Authors and affiliations

  • Shangzhu Jin
    • 1
  • Qiang Shen
    • 2
  • Jun Peng
    • 3
  1. 1.College of Electrical and Information EngineeringChongqing University of Science and TechnologyChongqingChina
  2. 2.Institute of Mathematics, Physics and Computer ScienceAberystwyth UniversityAberystwythUnited Kingdom
  3. 3.College of Electrical and Information EngineeringChongqing University of Science and TechnologyChongqingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-13-1654-8
  • Copyright Information Springer Nature Singapore Pte Ltd. 2019
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-13-1653-1
  • Online ISBN 978-981-13-1654-8
  • Buy this book on publisher's site