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Conference Paper
Development of a CNN-based Expert System using Domain Knowledge
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- Authors
- WonJong Kim, DongMug Kang, SungJae Yoon, Hanjin Cho, ChulHoo Kim, Jaemin Byun
- Issue Date
- 2019-06
- Citation
- International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2019, pp.829-830
- Language
- English
- Type
- Conference Paper
- Project Code
- 19PT1100, Development of Knowledge-Base Framework for Manufacturing Innovation and Optimal Management based on AI Technology, Kim Wonjong
- Abstract
- This paper describes development of a CNN-based expert system which can be used in smart factory applications such as automatic facilities control. In real situation, human experts control facilities with different values for the same input conditions, since there are tolerances for the control rather than exact values. So, when we develop system, domain knowledge is important. We used these knowledges of experts in preprocessing. To consider experts knowledge, we used average and median values in min/max range for each input pattern. The core algorithm of the expert system uses CNN-model. Final results are also evaluated based on expert's knowledge. Experimental results show that the proposed expert system can recommend control values with accuracy of 81.8% for the values and 98% for the min/max ranges, respectively. Also our recommend system has less outlier values compared with expert's ones.
- KSP Keywords
- Input pattern, Recommend System, Smart Factory, domain knowledge, expert system, real situation