한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

한국컴퓨터정보학회 (Korean Society of Computer Information)
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Feature Impact Evaluation Based Pattern Classification System

  • Rhee, Hyun-Sook (Dept. of Software Engineering, Dongyang Mirae University)
  • 투고 : 2018.09.12
  • 심사 : 2018.11.07
  • 발행 : 2018.11.30
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초록

Pattern classification system is often an important component of intelligent systems. In this paper, we present a pattern classification system consisted of the feature selection module, knowledge base construction module and decision module. We introduce a feature impact evaluation selection method based on fuzzy cluster analysis considering computational approach and generalization capability of given data characteristics. A fuzzy neural network, OFUN-NET based on unsupervised learning data mining technique produces knowledge base for representative clusters. 240 blemish pattern images are prepared and applied to the proposed system. Experimental results show the feasibility of the proposed classification system as an automating defect inspection tool.

키워드

CPTSCQ_2018_v23n11_25_f0002.png 이미지

Fig. 1. Feature Impact Evaluation Based Pattern Classification Model

Table 1. Feature information

CPTSCQ_2018_v23n11_25_t0001.png 이미지

Table 2. Features Rank Based on Feature Impact Evaluation

CPTSCQ_2018_v23n11_25_t0002.png 이미지

Table 3. Comparison of Classification Accuracy

CPTSCQ_2018_v23n11_25_t0003.png 이미지

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