Forecasting the daily electricity consumption in the Moscow region using artificial neural networks

Author:

Ivanov V. V.,Kryanev A. V.,Osetrov E. S.

Publisher

Pleiades Publishing Ltd

Subject

Radiology, Nuclear Medicine and imaging,Nuclear and High Energy Physics,Atomic and Molecular Physics, and Optics,Radiation

Reference26 articles.

1. V. V. Ivanov and E. S. Osetrov, “Forecasting of passenger traffic in Moscow metro applying artificial neural networks,” Vestn. MIFI 5, 65–74 (2016).

2. V. V. Ivanov and E. S. Osetrov, “Forecasting of the Moscow metro passenger traffic applying artificial neural networks with preliminary filtering analyzed data,” Vestn. MIFI 5, 162–169 (2016).

3. S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd ed. (Prentice Hall, Upper Saddle River, NJ, 1999).

4. B. Denby, “Tutorial on neural networks applications in high energy physics: 1982 perspective,” in New Computing Techniques in Physics Research II, Proceedings of the 2nd International Workshop on Software Engineering, Artifical Intelligence and Expert System in High Energy Physics, La Londe-les-Maures, France, Jan. 13–18, 1992, Ed. by D. Perret-Gallix (World Scientific, 1992), p. 287.

5. S. F. Fogelman, “Neural networks for patterns recognition: introduction and comparison to other techniques,” in New Computing Techniques in Physics Research II, Proceedings of the 2nd International Workshop on Software Engineering, Artifical Intelligence and Expert System in High Energy Physics, La Londe-les- Maures, France, Jan. 13–18, 1992, Ed. by D. Perret-Gallix (World Scientific, 1992), p. 277.

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