Abstract
Forecasting is an important study in the field of Supply Chain and Logistics for Operations Management. Based on a study a systematic framework has been worked and has been proposed for the same. Artificial Neural Network has been into this field and has been utilized for an efficient way to forecast and reduce errors marginally. The purpose of such a systematic approach using the proposed architecture is to reduce inventory holdings which shall largely account for important decision-making policies in the future.
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Prahathish, K., Naren, J., Vithya, G., Akhil, S., Dinesh Kumar, K., Sai Krishna Mohan Gupta, S. (2020). A Systematic Frame Work Using Machine Learning Approaches in Supply Chain Forecasting. In: Dehuri, S., Mishra, B., Mallick, P., Cho, SB., Favorskaya, M. (eds) Biologically Inspired Techniques in Many-Criteria Decision Making. BITMDM 2019. Learning and Analytics in Intelligent Systems, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-39033-4_15
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