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| HAL : hal-00717189, version 1 |
| DOI : 10.1016/j.eswa.2012.02.135 |
| Fiche détaillée |  Récupérer au format |
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| Expert Systems with Applications 39, 16 (2012) Pages 12302-12309 |
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| Financial time series forecasting with a bio-inspired fuzzy model |
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| José-Luis Aznarte 1Jesús Alcalá-Fdez 2 |
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| (11/2012) |
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| In general, times series forecasting is considered as a highly complex problem, which is particularly true for financial time series. In this paper, a fuzzy model evolved through a bio-inspired algorithm is proposed to produce accurate models for the prediction of these time series. The performance of this model is compared to that of a group of state-of-the-art statistical models. A thorough experimental study is designed and carry out in order to assess the merits of the proposal. The experimental results allow us to state that our proposal forecasts consistently outperform the other considered methods. |
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| 1 : | Centre Énergétique et Procédés (CEP) |
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MINES ParisTech - École nationale supérieure des mines de Paris |
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| 2 : | Department of Computer Science and Artificial Intelligence (DECSAI) |
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University of Granada |
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| 3 : | Department of Civil Engineering |
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University of Córdoba |
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| CEP/Sophia MINES ParisTech BP 207 - Rue Claude Daunesse - 06904 Sophia Antipolis Cedex - France - http://www.mines-paristech.fr/Fr/CEP/ |
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| Domaine | : | Sciences de l'ingénieur/Energétique Sciences de l'environnement/Planification énergétique |
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| Financial time series – Fuzzy rule-based systems – Regime switching models – Time series forecasting |
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| hal-00717189, version 1 | |
| http://hal-ensmp.archives-ouvertes.fr/hal-00717189 | |
| oai:hal-ensmp.archives-ouvertes.fr:hal-00717189 | |
| Contributeur : Brigitte Hanot | |
| Soumis le : Jeudi 12 Juillet 2012, 11:01:27 | |
| Dernière modification le : Mardi 14 Août 2012, 14:26:45 | |
