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인공신경망을 이용한 항만터미널에서 컨테이너의 비정상 이송 프로세스 예측
전대욱(Daeuk Jeon),배혜림(Hyerim Bae) 한국SCM학회 2015 한국SCM학회지 Vol.15 No.2
There has been a request for improvement of container transfer in container terminal, because there is a complexity of work processes and cargo features of container. This paper is addressing the issue of abnormal process prediction using event logs which is occurred by an action of container transfer. Event logs contain the historical data from the executed processes. So, the analysis must be performed after the finished container transfer process. Hence, it is hardly avoidable that there is a time gap between analyzing and applying the analysis result. To reduce this time gap, we suggest a usage of ANN (Artificial Neural Network) for forecasting the anomalous container transfer. We use ARM (Activity Relation Matrix), a distance measure and LAPID (Local Anomaly Process Instance Detection) methodology to detect API (Anomaly Process Instance). The effectiveness of the proposed method was verified in a case study using real event logs from domestic container terminal.