Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Fuzzy Model on the PNN Structure and its Applications

  • Sang, R.S. (Dept. of Control and Instrumentation Eng, Wonkwang Univ.) ;
  • Oh, Sungkwun (Dept. of Control and Instumentation Eng. Wonksang Univ) ;
  • Ahn, T.C. (Dept. of Control and Instrumentation Eng. Wonkwang Univ.)
  • Published : 1997.10.01
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Abstract

In this paper, a fuzzy model based on the polynomial Neural Network(PNN) structure is proposed to estimate the emission pattern for air pollutant in power plants. The new algorithm uses PNN algorithm based on Group Method of Data Handling (GMDH) algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the least square method in order to identify the optimal consequence parameters. Both time series data for the gas furnace and data for the NOx emission process of gas turbine power plants are used for the purpose of evaluating the performance of the fuzzy model. The simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy anhd feasibility than other works achieved previously.

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