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- W1566006507 abstract "We present a not fully connected recurrent network applied to the problem of load forecasting. Although many authors have pointed out that recurrent networks were able to model NARMAX processes, we present a constructing scheme for the MA part. In addition we present a modification of the learning step which improves learning convergence and the accuracy of the forecast. At last, the use of a continuous learning scheme and a robust learning scheme, which appeared to be necessary when using a MA part, enables us to reach a good precision of the forecast, compared to the accuracy of the model in use at the utility at present." @default.
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- W1566006507 date "2002-11-19" @default.
- W1566006507 modified "2023-10-16" @default.
- W1566006507 title "Improving recurrent network load forecasting" @default.
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- W1566006507 doi "https://doi.org/10.1109/icnn.1995.487538" @default.
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