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학술지 자기 유사성 기반 소포 우편 단기 물동량 예측 모형 연구
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저자
김은혜, 정훈
발행일
202012
출처
산업경영시스템학회지, v.43 no.4, pp.76-83
ISSN
2005-0461
출판사
한국산업경영시스템학회
DOI
https://dx.doi.org/10.11627/jkise.2020.43.4.076
협약과제
20HR3400, 우편물류 인프라 기술개발, 정훈
초록
Postal logistics organizations are characterized as having high labor intensity and short response times. These characteristics, along with rapid change in mail volume, make load scheduling a fundamental concern. Load analysis of major postal infrastructures such as post offices, sorting centers, exchange centers, and delivery stations is required for optimal postal logistics operation. In particular, the performance of mail traffic forecasting is essential for optimizing the resource operation by accurate load analysis. This paper addresses a traffic forecast problem of postal parcel that arises at delivery stations of Korea Post. The main purpose of this paper is to describe a method for predicting short-term traffic of postal parcel based on self-similarity analysis and to introduce an application of the traffic prediction model to postal logistics system. The proposed scheme develops multiple regression models by the clusters resulted from feature engineering and individual models for delivery stations to reinforce prediction accuracy. The experiment with data supplied by main postal delivery stations shows the advantage in terms of prediction performance. Comparing with other technique, experimental results show that the proposed method improves the accuracy up to 45.8%.
KSP 제안 키워드
Load Analysis, Load scheduling, Logistics operation, Multiple Regression, Prediction accuracy, Regression Model, Traffic Prediction, Traffic forecasting, feature engineering, logistics system, prediction model