Hierarchical Qualitative Inference Model with Substructures

  • Zehua Zhang
  • Duoqian Miao
  • Jin Qian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6954)

Abstract

Qualitative propagation influences in qualitative inferences are unlike and interrelated on the different hierarchy of knowledge granules, and quantitative information loss easily results in reasoning conflicts. This paper presents a hierarchical qualitative inference model with substructures which to some extent can eliminate the qualitative impact of uncertainty and solve trade-off problems by metastructures with basic decomposition and coarse-grained mesoscale substructures with edge-deletion. The substructural inferences could not only reduce computational complexity, but provide an approximate strategy for modular reasoning on large-scale problems. The example respectively illustrates the two substructural methods are both effective.

Keywords

qualitative inference substructures hierarchical structure granular computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Zehua Zhang
    • 1
    • 2
  • Duoqian Miao
    • 1
  • Jin Qian
    • 1
  1. 1.Department of Computer Science and TechnologyTongji UniversityShanghaiChina
  2. 2.College of Computer Science and TechnologyTaiyuan University of TechnologyShanxiChina

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