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Energy consumption forecasting for power supply companiesThe paper investigates an issue of the accuracy of energy consumption forecasts for power supply
USE OF NEURONIC NETWORK TO FORECAST POWER CONSUMPTION DURING TRANSPORTATION OF OIL by mathematical statistics methods using actual data. The task was set to forecast power consumption for oil
Improving the Energy Efficiency of Electricity Distribution in the Mining Industry Using Distributed Generation by Forecasting Energy Consumption Using Machine Learning. The article describes analysis of methods of power consumption forecasting, as well as factors that are taken
ALGORITHM OF THE DECISION OF THE PROBLEM OF FORECASTING POWER CONSUMPTION IN PIPELINE TRANSPORT OF OIL WITH USE OF NEURAL NETWORKSWork is devoted forecasting of the expense of the electric power in planning of operating modes
The basic aspects of neural network forecasting model of the electric power consumption for developing oil pipelinesThe work is devoted to forecasting of electricity consumption in the planning period of operation
Методы решения задач оценки и прогнозирования энергетической эффективности power consumption modes, it was found that the theoretical data practically coincides with the actual
Development of Forecasting Models to Manage the Power Consumption Modes of the Gas Industry FacilitiesThe paper proposes the solution to the problem of forecasting the power load for various gas
Прогнозирование и повышение энергетической эффективности предприятий водопроводно-канализационного хозяйстваForecasting and improving the energy efficiency of water supply and sewerage enterprises
Electric Energy Consumption Modes Forecasting and Management for Gas Industry Enterprises Based on Artificial Intelligence MethodsThis paper shows the electrical load forecast problem solution for gas industry enterprises, taking
Energy Economy Potential Estimation of Establishment Needs Objects of Power Distribution Company out, a mathematical model of power consumption was obtained. The procedures of interval estimation
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