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- W1985776722 abstract "This paper presents a neuro-based short term load forecasting (STLF) method for Iran National Power System (INPS) and its regions. The architecture of the proposed network is a three-layer feed forward neural network whose parameters are tuned by Levenberg-Marquardt BP (LMBP) augmented by an early stopping (ES) method tried out for increasing the speed of convergence. Instead of seasonal training, an input as a month indicator is added to the input vectors. The short term load forecasting simulator developed so far presents satisfactory and better results for one hour up to a week prediction of INPS loads and region of INPS, Bakhtar Region Electric Co (BREC). This paper is compared with another one." @default.
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- W1985776722 date "2006-12-01" @default.
- W1985776722 modified "2023-10-18" @default.
- W1985776722 title "A New Short Term Load Forecasting Using Multilayer Perceptron" @default.
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- W1985776722 doi "https://doi.org/10.1109/icinfa.2006.374131" @default.
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