Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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Effective Gas Identification Model based on Fuzzy Logic and Hybrid Genetic Algorithms

  • Bang, Yonug-Keun (New Regeneration Research Center, Kangwon National University) ;
  • Byun, Hyung-Gi (Division of Electronics, Information & Communication Eng., Kangwon National University) ;
  • Lee, Chul-Heui (Dept. of Electrical & Electronics Eng., Kangwon National University)
  • Received : 2012.07.25
  • Accepted : 2012.09.13
  • Published : 2012.09.30
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Abstract

This paper presents an effective design method for a gas identification system. The design method adopted the sequential combination between the hybrid genetic algorithms and the TSK fuzzy logic system. First, the sensor grouping method by hybrid genetic algorithms led the effective dimensional reduction as well as effective pattern analysis from a large volume of pattern dimensions. Second, the fuzzy identification sub-models allowed handling the uncertainty of the sensor data extensively. By these advantages, the proposed identification model demonstrated high accuracy rates for identifying the five different types of gases; it was confirmed throughout the experimental trials.

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References

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