Темир йўл транспорти: долзарб масалалар ва инновациялар Volume 4 Issue 4 (2023) · pp. 42-46
NEURAL NETWORKS IN PREDICTING ELECTRICAL LOAD IN RAILWAY TRANSPORT: NEURAL NETWORKS IN PREDICTING ELECTRICAL LOAD IN RAILWAY TRANSPORT
Турдибеков, К.Х., Рустамов, Д.Ш.
Abstract
Forecasting the electrical load provides the main basis for decision-making when managing the power supply system of railway transport. In this case, it is necessary to find the initial and optimal modes, evaluate their reliability, efficiency and energy quality. Existing algorithms used to predict electrical loads in the railway power supply system are based on statistical methods, as well as on considering changes in electrical loads as random processes. All these methods cannot really describe the forecasting process due to the fact that there are incomplete source data. All this gives rise to the use of neural network methods with fuzzy logic to predict changes in electrical loads in the power supply system of railway transport. It was found that this method is optimal for predicting electrical loads.
искусственные нейронные сети, системы с нечеткой логикой, алгоритм прогнозирования, системы электроснабжения, электрические нагрузки, обучающие сети.Аrtificial neural networks, fuzzy logic systems, forecasting algorithm, power supply systems, electrical loads, learning networks.
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