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Generating and Applying Rules for Interval Valued Fuzzy Observations

  • Andre de Korvin
  • Chenyi Hu
  • Ping Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3177)

Abstract

One of the objectives of intelligent data engineering and automated learning is to develop algorithms that learn the environment, generate rules, and take possible courses of actions. In this paper, we report our work on how to generate and apply such rules with a rule matrix model. Since the environments can be interval valued and rules often fuzzy, we further study how to obtain and apply rules for interval valued fuzzy observations.

Keywords

Membership Function Fuzzy System Fuzzy Subset Interval Arithmetic Interval Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Andre de Korvin
    • 1
  • Chenyi Hu
    • 2
  • Ping Chen
    • 1
  1. 1.Department of Computer and Mathematical SciencesUniversity of Houston-DowntownHoustonUSA
  2. 2.Department of Computer ScienceUniversity of Central ArkansasConwayUSA

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