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- W2474855966 abstract "An automated system is described for designing neural networks for very short term power load forecasting. The system consists of three parts which are; the signal conditioner, the network sizer, and the trainer. The signal conditioning subsystem averages power over one minute intervals to reduce noise and generates training data for the neural network. This includes past powers and the time of day. The network sizer uses a fast complexity estimation algorithm to estimate the required number of neutral network hidden units. The trainer trains the neutral net. The system is demonstrated on data supplied by an electric utility. Although the training data and testing data sets are disjoint and show significant differences, the neural networks produced by the system successfully predict the load." @default.
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- W2474855966 date "1996-10-01" @default.
- W2474855966 modified "2023-09-24" @default.
- W2474855966 title "An automated system for developing neural network short term load forecasters" @default.
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