Table_1.xls (9.5 kB)

Metrics for forecasting assessment, where N is the size of the series, target_j is the real value at period j, output_j is the forecasting at period j and target¯ is the mean of the series.

dataset

posted on 2015-09-28, 03:21 authored by Paulo S. G. de Mattos Neto, George D. C. Cavalcanti, Francisco Madeiro, Tiago A. E. Ferreira

In the column θ: ↑ means the higher the value of metric the better is the forecasting, and ↓ means the lower the value of metric the better is the forecasting.

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An Approach to Improve the Performance of PM Forecasters

PLOS ONE

Keywords

ga Artificial neural networks approach correction PM 10 concentration series High PM concentration hs residuals modeling fitness function ann PM forecasters forecasting method performance Experimental results show PM time series

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CC BY 4.0

Metrics for forecasting assessment, where N is the size of the series, target_j is the real value at period j, output_j is the forecasting at period j and target¯ is the mean of the series.

History

Usage metrics

Read the peer-reviewed publication

Categories

Keywords

Licence

Exports

Metrics for forecasting assessment, where N is the size of the series, targetj is the real value at period j, outputj is the forecasting at period j and target¯ is the mean of the series.

History

Usage metrics

Read the peer-reviewed publication

Categories

Keywords

Licence

Exports

Metrics for forecasting assessment, where N is the size of the series, target_j is the real value at period j, output_j is the forecasting at period j and target¯ is the mean of the series.