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復雜過程分析的模糊聚類分類器設計及其性能

Design of Fuzzy Classifier for Complicated Process Analysis and Its Performance

  • 摘要: 本文采用模式識別方法推斷燒結礦質量。在給出模糊系統聚類分析算法基礎上,用軟件實現了基于模糊聚類分類器和動態聚類分類器,并用現場實測的樣本采用"留一法"分別對這兩種分類器性能進行檢驗。結果表明:模糊聚類分析法對于先驗知識較少、樣本量不大時,性能較佳。

     

    Abstract: Application of pattern recognition and AI is a promisive approach to this problem. In the paper, pattern recognition method is used to test the quality of sinter. On the basis of the algorithm of fuzzy clustering analysis, the classifiers based on fuzzy clustering and dynamic state clustering in microcomputer are set up. The performance of the classifiers is tested. The results show that, in the case of lacking priori knowledge, fuzzy clustering analysis is superior to dynamic state clustering analysis when the number of samples is small.

     

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