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Fig 1.

Ridge Polynomial Neural Network.

PSNN stands for Pi-Sigma Neural Network.

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Fig 1 Expand

Fig 2.

Dynamic Ridge Polynomial Neural Network.

PSNN stands for Pi-Sigma Neural Network and Z−1 denotes the time delay operator.

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Fig 2 Expand

Fig 3.

Ridge Polynomial Neural Network with Error Feedback.

PSNN stands for Pi-Sigma Neural Network, d(t + 1) is the desired output at time t + 1 and Z−1 denotes the time delay operator.

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Fig 3 Expand

Table 1.

Time series information.

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Table 1 Expand

Fig 4.

Star brightness time series.

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Fig 4 Expand

Fig 5.

Monthly smoothed sunspot numbers time series from November 1834 to June 2001.

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Fig 5 Expand

Fig 6.

Daily Euro/Dollar exchange rate time series from January 3, 2005 to December 31, 2007.

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Fig 6 Expand

Fig 7.

Mackey–Glass time-delay differential equation time series.

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Fig 7 Expand

Table 2.

Network topology and training.

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Table 2 Expand

Table 3.

Root Mean Squared Error (RMSE) improvement of RPNN-EF to RPNN and DRPNN.

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Table 3 Expand

Table 4.

Normalized Mean Squared Error (NMSE) improvement of RPNN-EF to RPNN and DRPNN.

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Table 4 Expand

Table 5.

Mean Absolute Error (MAE) improvement of RPNN-EF to RPNN and DRPNN.

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Table 5 Expand

Table 6.

Signal to Noise Ratio (SNR) improvement of RPNN-EF to RPNN and DRPNN.

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Table 6 Expand

Fig 8.

Network order for the best average simulations on the used time series.

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Fig 8 Expand

Table 7.

Best Single Simulation Results.

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Table 7 Expand

Fig 9.

Correlation function between forecast and observed values for StarBrightness time series based on the best RPNN-EF simulation.

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Fig 9 Expand

Fig 10.

Correlation function between forecast and observed values for Sunspot time series based on the best RPNN-EF simulation.

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Fig 10 Expand

Fig 11.

Correlation function between forecast and observed values for EUR/USD time series based on the best RPNN-EF simulation.

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Fig 11 Expand

Fig 12.

Correlation function between forecast and observed values for Mackey–Glass time series based on the best RPNN-EF simulation.

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Fig 12 Expand

Fig 13.

Out-of-sample forecasting for StarBrightness time series based on the best RPNN-EF simulation.

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Fig 13 Expand

Fig 14.

Out-of-sample forecasting for Sunspot time series based on the best RPNN-EF simulation.

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Fig 14 Expand

Fig 15.

Out-of-sample forecasting for EUR/USD time series based on the best RPNN-EF simulation.

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Fig 15 Expand

Fig 16.

Out-of-sample forecasting for Mackey–Glass time series based on the best RPNN-EF simulation.

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Fig 16 Expand

Fig 17.

The histogram of the forecasting error for StarBrightness time series based on the best RPNN-EF simulation.

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Fig 17 Expand

Fig 18.

The histogram of the forecasting error for Sunspot time series based on the best RPNN-EF simulation.

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Fig 18 Expand

Fig 19.

The histogram of the forecasting error for EUR/USD time series based on the best RPNN-EF simulation.

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Fig 19 Expand

Fig 20.

The histogram of the forecasting error for Mackey–Glass time series based on the best RPNN-EF simulation.

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Fig 20 Expand

Table 8.

Comparison of the performance of various existing models on Sunspot series.

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Table 8 Expand

Table 9.

Comparison of the performance of various existing models on Mackey–Glass series.

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Table 9 Expand

Fig 21.

Learning curves for StarBrightness time series forecasting based on the best RPNN-EF simulation.

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Fig 21 Expand

Fig 22.

Learning curves for Sunspot time series forecasting based on the best RPNN-EF simulation.

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Fig 22 Expand

Fig 23.

Learning curves for Daily Euro/Dollar (EUR/USD) exchange rate time series forecasting based on the best RPNN-EF simulation.

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Fig 23 Expand

Fig 24.

Learning curves for Mackey–Glass time series forecasting based on the best RPNN-EF simulation.

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Fig 24 Expand