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NTIS 바로가기Journal of the convergence on culture technology : JCCT = 문화기술의 융합, v.9 no.3, 2023년, pp.763 - 768
김희영 (광운대학교 대학원 실감융합콘텐츠학과) , 류기환 (광운대학교 스마트융합대학원) , 근재 (광운대학교 대학원 실감융합콘텐츠학과) , 손현곤 (광운대학교 대학원 실감융합콘텐츠학과)
In this paper, the existing statistical method (ARIMA) and machine learning method (Informer) were developed and compared to predict the distribution volume of pharmaceuticals. It was found that a machine learning-based model is advantageous for daily data prediction, and it is effective to use ARIM...
Rathipriya, R., et al., "Demand forecasting model?for time-series pharmaceutical data using shallow?and deep neural network model.", Neural Computing?and Applications, Vol. 35, No. 2, pp. 1945-1957,?2023. DOI: https://doi.org/10.1007/s00521-022-07889-9
Zhu, Xiaodan, et al., "Demand forecasting with?supply-chain information and machine learning:?Evidence in the pharmaceutical industry.",?Production and Operations Management, Vol. 30,?No. 9, pp. 3231-3252, March 2021. DOI: https://doi.org/10.1111/poms.13426
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Zhou, Haoyi, et al., "Informer: Beyond efficient?transformer for long sequence time-series?forecasting.", Proceedings of the AAAI conference?on artificial intelligence, Vol. 35, No. 12, pp.?11106-11115, 2021. DOI: https://doi.org/10.1609/aaai.v35i12.17325
H. Y. Kim, S. M. Jung, W. S. Kim, G. H. Ryu,?H. K. Son, "A Study on the Implementation of?Restaurant Recommendation System based on?Deep Learning-based Consumer Data", The Journal?of Convergence of Culture Technology (JCCT),?Vol. 7, No. 2, pp. 437-442, 2021. DOI: http://dx.doi.org/10.17703/JCCT.2021.7.2.437
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