Articles liés à NEW ALGORITHMS FOR MULTI-STEP AHEAD FORECASTING: Using...

NEW ALGORITHMS FOR MULTI-STEP AHEAD FORECASTING: Using Computational Intelligence Paradigm - Couverture souple

Arif, Muhammad; Rahat, Syed

 
9783639249811: NEW ALGORITHMS FOR MULTI-STEP AHEAD FORECASTING: Using Computational Intelligence Paradigm
Couverture souple
ISBN 10 : 363924981X ISBN 13 : 9783639249811
Editeur : VDM Verlag Dr. Müller, 2010

Synopsis

History tells that every human being desire to foresee, comprehend and ultimately explore the future. Multi-step ahead forecasting is a challenging research area due to propagation of forecasting errors with the increase of forecasting steps. Two interesting architectures based on nearest neighbor method are proposed. Importance of selection criteria in nearest neighbor search plays an important role in multi-step ahead forecasting. Effect of up-sampling of time series and change of effective embedding dimension on the forecasting errors is studied in detail. Effect of five interpolation schemes for up-sampling and comparison of three distance metrics for nearest neighbor search on forecasting performance is also included. A hybrid selection criterion of nearest neighbor with avoidance of biasing is found to be very effective in multi-step ahead forecasting. In the end, predictability analysis of proposed algorithms on ten benchmark time series highlight the effectiveness of the forecasting algorithms in the scenarios of series collected from different kinds of dynamic systems. This book is based on the PhD work of Mr. Rahat Abbas.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

History tells that every human being desire to foresee, comprehend and ultimately explore the future. Multi-step ahead forecasting is a challenging research area due to propagation of forecasting errors with the increase of forecasting steps. Two interesting architectures based on nearest neighbor method are proposed. Importance of selection criteria in nearest neighbor search plays an important role in multi-step ahead forecasting. Effect of up-sampling of time series and change of effective embedding dimension on the forecasting errors is studied in detail. Effect of five interpolation schemes for up-sampling and comparison of three distance metrics for nearest neighbor search on forecasting performance is also included. A hybrid selection criterion of nearest neighbor with avoidance of biasing is found to be very effective in multi-step ahead forecasting. In the end, predictability analysis of proposed algorithms on ten benchmark time series highlight the effectiveness of the forecasting algorithms in the scenarios of series collected from different kinds of dynamic systems. This book is based on the PhD work of Mr. Rahat Abbas.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2010
Langue
anglais
ISBN 10 
363924981X
ISBN 13 
9783639249811
Reliure
Broché
Nombre de pages
160
Coordonnées du fabricant
non disponible
Personne responsable
non disponible