[논문]Disapproval Judgment System of Research Fund Execution Details Based on Artificial Intelligence

Kim, Yongkuk; Juan, Tan; Jung, Hoekyung

doi:10.6109/jicce.2021.19.3.142

Disapproval Judgment System of Research Fund Execution Details Based on Artificial Intelligence 원문보기

Journal of information and communication convergence engineering, v.19 no.3, 2021년, pp.142 - 147

Kim, Yongkuk (KEIT) , Juan, Tan (Weifang University of Science and Technology) , Jung, Hoekyung (Department of Computer Engineering, Paichai University)

Abstract ▼ AI-Helper

In this paper, we propose an intelligent research fund management system that applies artificial intelligence technology to an integrated research fund management system. By defining research fund management rules as work rules, a detection model learned using deep learning is designed, through which the disapproval status is presented for each research fund usage history. The disapproval detection system of the RCMS implemented in this study predicts whether the newly registered usage details are recognized or disapproved using an artificial intelligence model designed based on the use of an 8.87 million research fund registered in the RCMS. In addition, the item-detail recommendation system described herein presents the usage details according to the usage history item newly registered by the artificial intelligence model through a correlation between the research cost usage details and the item itself. The accuracy of the recommendation was shown to be 97.21%.

주제어

표/그림 (8)

그림 Fig. 1. Configuration diagram of disapproval detection system.
그림 Fig. 4. Learning graphs for (a) recall and RWN and (b) precision and RWN.
그림 Fig. 2. Structure of disapproval detection model.
그림 Fig. 3. Learning graph for loss values of an RWN.
그림 Fig. 5. Configuration diagram of recommendation system for research expenditure items.
표 Table 1. Performance of RWN with CE by threshold
표 Table 2. Results of 10-fold cross-validation for SVM
표 Table 3. Results of 10-fold cross-validation for WE

참고문헌 (8)

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상세보기
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원문보기 상세보기
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원문보기 상세보기
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