Universal energy consumption forecasting system based on neural network ensemble


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Problems of neural network forecasting system, invariant to type of energy consumption schedule are solved. Minimum length input vector structure is explained; neural network ensemble structures are determined; selection of the most effective neural network types in the ensemble is held. Original three-level structure of neural network ensemble is developed. Its high forecasting capability makes network perspective for solving information statistical analysis problems.

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B. Staroverov

Kostroma State University of Technology

编辑信件的主要联系方式.
Email: sba44@mail.ru
俄罗斯联邦, Kostroma

B. Gnatyuk

Kostroma State University of Technology

Email: sba44@mail.ru
俄罗斯联邦, Kostroma

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