Forecasting the electric consumption of objects using artificial neural networks

Abstract

The possibility of using artificial neural networks of the Matlab mathematical package for predicting the power consumption of objects is considered, the parameters that affect the power consumption are studied.

Influence of γ – radiation on the properties of silicon with clusters impurity atoms of manganese and nickel

“…1, curves 4, 5). As can be seen from the figure, in these samples a noticeable change in the resistivity begins at sufficiently high doses , and with an increase in the irradiation dose, the resistivity does not decrease, as in the case of samples with nanoclusters, but increases to the value of intrinsic silicon [8][9][10][11][12][13][14].…”

Loading mode of a ferromagnetic current stabilizer

“…In order to clarify the influence of various load parameters on the operation of the ferrimagnetic current stabilizer and to assess the energy and performance indicators, we will consider the load mode of the device. Taking assumptions and neglecting losses in the magnetic amplifier, we will analyze the steady state for active, activeinductive and active-capacitive loads [1][2][3][4][5][6][7].…”

Algorithm for estimating the mode and electricity losses in distribution electric networks 6-110 kV conditions of incomplete information

“…When performing calculations of the steady state and energy losses in distribution networks of 6-110 kV, we are faced with a lack of circuit and mode information. At the same time, to perform calculations, it is possible to use methods that allow taking into account the features of the information support of networks of this class [1][2][3][4][5][6][7].…”