Artificial intelligence and quantum computing models for forecasting processes in power supply systems

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dc.contributor.authorShevchenko, V.
dc.contributor.authorShmatko, O. V.
dc.contributor.authorШевченко, В.
dc.contributor.authorШматко, О. В.
dc.date.accessioned2026-03-01T19:44:33Z
dc.date.issued2025
dc.description.abstractAccurate forecasting of power supply parameters is one of the most fundamental tasks in modern energy system management [1]. The increasing penetration of renewable energy sources, the variability of consumer demand, and the transition to decentralized smart grids have introduced unprecedented complexity into the operation of power systems. Traditional forecasting methods, including statistical regression, time series analysis, and classical machine learning algorithms, often struggle to capture the nonlinear and transient dynamics of such systems.
dc.identifier.citationShevchenko V., Shmatko O. V. Artificial intelligence and quantum computing models for forecasting processes in power supply systems. Актуальні питання розвитку галузей науки : наукові праці з матеріалами VI Міжнародної наукової конференції, м. Вінниця, 31жовтня 2025 р. Вінниця, 2025. С. 395-397.
dc.identifier.urihttps://dspace.mipolytech.education/handle/mip/3557
dc.language.isoen
dc.publisherГО «Міжнародний центр наукових досліджень»
dc.titleArtificial intelligence and quantum computing models for forecasting processes in power supply systems
dc.typeThesis

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