Hierarchical qualitative inference model with substructures

Authors:
Zehua Zhang;Duoqian Miao;Jin Qian
Affiliations:
Department of Computer Science and Technology, Tongji University, Shanghai, China and College of Computer Science and Technology, Taiyuan University of Technology, Shanxi, China;Department of Computer Science and Technology, Tongji University, Shanghai, China;Department of Computer Science and Technology, Tongji University, Shanghai, China
Venue:
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Year:
2011

Citing 11
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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.