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Granular Fuzzy Inference System (FIS) Design by Lattice Computing

  • Vassilis G. Kaburlasos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6077)

Abstract

Information granules are partially/lattice-ordered. Therefore, lattice computing (LC) is proposed for dealing with them. The granules here are Intervals’ Numbers (INs), which can represent real numbers, intervals, fuzzy numbers, probability distributions, and logic values. Based on two novel theoretical propositions introduced here, it is demonstrated how LC may enhance popular fuzzy inference system (FIS) design by the rigorous fusion of granular input data, the sensible employment of sparse rules, and the introduction of tunable nonlinearities.

Keywords

Fuzzy inference system (FIS) Granular data Inclusion measure Intervals’ number (IN) Lattice computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Vassilis G. Kaburlasos
    • 1
  1. 1.Department of Industrial InformaticsTechnological Educational Institution of KavalaKavalaGreece

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