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https://doi.org/10.1109/itc-cscc.2019.8793323
Copy DOIPublication Date: Jun 1, 2019 |
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.
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