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- W2536804968 abstract "Forecasting model has been applied in many areas of study. Neural Network (NN) is the most popular forecasting model among the intelligent methods. However, NN had some limitations in learning patterns which have terrific noise and nonlinear characteristic. This paper aims to analyze the performances of NN forecasting model using data that have been smoothed. The actual data were smoothed by three exponential smoothing techniques and normalized before the experiment. One NN model was developed and tested with ten different hidden units. The percentage of correctness and mean absolute error gathered from NN training were used to evaluate the NN performance. The findings show that the NN model using smoothed data gives better performance compared to actual data." @default.
- W2536804968 created "2016-10-28" @default.
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- W2536804968 date "2016-01-01" @default.
- W2536804968 modified "2023-09-25" @default.
- W2536804968 title "Neural network forecasting model using smoothed data" @default.
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- W2536804968 doi "https://doi.org/10.1063/1.4966079" @default.
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