MACHINE LEARNING FOR FORECASTING DEMAND FOR ONLINE ORDERS

Authors

  • Nina Zdolbitska Lutsk National Technical University https://orcid.org/0000-0002-1345-3581
  • Andrii Zdolbitskyi Lutsk National Technical University
  • Denys Davydiuk Lutsk National Technical University

Keywords:

AI, Machine Learning, Data Analysis, Forecasting, Demand

Abstract

Decision-making based on the integration of artificial intelligence for demand forecasting is becoming a necessity with the significant development of e-commerce. Businesses that implement AI technologies are well-adapted to market changes and achieve success in e-commerce, as well as satisfy customer expectations.

References

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Zdolbitska N., Heiko B., Mitsura Yu. Client-server application for planning and production scheduling based on WPF. Матеріали VІІІ Міжнародної науково-практичної конференції «Інформаційна безпека та комп’ютерні технології»: тези доповідей, 24-25 квітня 2025. м. Кропивницький: ЦНТУ. 2025. С. 32.

Nina Zdolbitska, Oleksandr Ostapchuk, Svitlana Lavrenchuk, Taras Terletskyi, Oleh Kaidyk, Oksana Zhyharevych. Business Information System for Forecasting Raw Material Stocks for the Production of Flexible Packaging. 14th International Conference on Dependable Systems, Services and Technologies (DESSERT). 2024.

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Yara Kayyali Elalem, Sebastian Maier, Ralf W. Seifert, A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks, International Journal of Forecasting, Volume 39, Issue 4, 2023, pp. 1874-1894, https://doi.org/10.1016/j.ijforecast.2022.09.005

Published

2025-06-03