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| Format: | Artículo científico |
| Language: | en |
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Instituto Politécnico Nacional
2006
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| Online Access: | https://www.redalyc.org/articulo.oa?id=61501106 |
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| _version_ | 1866586061859192832 |
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| author | María Angélica Salazar Aguilar |
| author_facet | María Angélica Salazar Aguilar |
| contents | Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case María Angélica Salazar Aguilar Guillermo J. Moreno Rodríguez Mauricio Cabrera-Ríos Computación Time Series Forecasting Artificial Neural Networks Design and Analysis of Experiments Time series forecasting is an active area for the application of Artificial Neural Networks (ANNs). Although the selection of an ANN has been greatly simplified, it remains a challenge to adequately determine the ANNs parameters. In this work a method based on statistical analysis and optimization techniques is proposed to select the ANN´s parameters for application in time series forecasting. The results on the successful application of the method in a real demand forecasting problem for the telecommunications industry are also reported. . 2006 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61501106 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.10 |
| format | Artículo científico |
| id | redalyc_61501106 |
| language | en |
| publishDate | 2006 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case María Angélica Salazar Aguilar Computación Time Series Forecasting Artificial Neural Networks Design and Analysis of Experiments Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case María Angélica Salazar Aguilar Guillermo J. Moreno Rodríguez Mauricio Cabrera-Ríos Computación Time Series Forecasting Artificial Neural Networks Design and Analysis of Experiments Time series forecasting is an active area for the application of Artificial Neural Networks (ANNs). Although the selection of an ANN has been greatly simplified, it remains a challenge to adequately determine the ANNs parameters. In this work a method based on statistical analysis and optimization techniques is proposed to select the ANN´s parameters for application in time series forecasting. The results on the successful application of the method in a real demand forecasting problem for the telecommunications industry are also reported. . 2006 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61501106 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.10 |
| title | Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case |
| topic | Computación Time Series Forecasting Artificial Neural Networks Design and Analysis of Experiments |
| url | https://www.redalyc.org/articulo.oa?id=61501106 |