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Universal energy consumption forecasting system based on neural network ensemble

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Abstract

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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Authors and Affiliations

  1. Kostroma State University of Technology, Kostroma, Russia

    B. A. Staroverov & B. A. Gnatyuk

Authors
  1. B. A. Staroverov
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  2. B. A. Gnatyuk
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Correspondence to B. A. Staroverov.

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Staroverov, B.A., Gnatyuk, B.A. Universal energy consumption forecasting system based on neural network ensemble. Opt. Mem. Neural Networks 25, 198–202 (2016). https://doi.org/10.3103/S1060992X16030097

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  • DOI: https://doi.org/10.3103/S1060992X16030097

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