Forecasting the wind speed process using higher order statistics and fuzzy systems

نویسندگان

  • J. Antari
  • R. Iqdour
  • A. Zeroual
چکیده

This investigation has two main objectives. The first one is to propose a statistical method, based on the fourth order cumulants, to identify single-input single-output ‘SISO’, finite impulse response ‘FIR’ system using non gaussian input, zero mean and independent identically distributed signals. The second objective is to search, as an application, a model for forecasting the wind speed time series and to compare the obtained results with those obtained using the TakagiSugeno ‘TS’ fuzzy techniques. The prediction results obtained by the proposed method show that the sequences of generated values have the same statistical characteristics as those really observed and better than those obtained using ‘TS’ fuzzy systems. Additionally, the model developed on the basis of the statistical method fits well wind speed time series and can be used for forecasting purpose with an accuracy of 94 % and above. Résumé Cette recherche a deux principaux objectifs. Le premier objectif est de proposer une méthode statistique, basée sur les cumulants d’ordre quatre, pour identifier le premier entrant et le premier sortant ‘SISO’ du système de réponse d’impulsion fini ‘FIR’, utilisant l’entrée non gaussienne, le zéro moyen et en signaux indépendants identiquement distribués. Le deuxième objectif est de rechercher, comme application, un modèle pour prédire la série chronologique de la vitesse de vent et de comparer les résultats obtenus à ceux obtenus en utilisant les techniques floues de TakagiSugeno ‘TS’. Les résultats de prévision obtenus par la méthode proposée prouvent que les séquences valeurs générées ont les mêmes caractéristiques statistiques que ceux réellement observés et sont meilleurs que ceux obtenus en utilisant les systèmes flous de ‘TS’. De plus, le modèle développé sur la base de la méthode statistique s’adapte correctement à la série chronologique de la vitesse de vent et peut être employé dans le but de prévision avec une précision de 94 % et plus.

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تاریخ انتشار 2006