Weighted Multi-view Deep Neural Networks for Weather Forecasting
| Autor: | Zahra Karevan, Johan A. K. Suykens, Lynn Houthuys |
|---|---|
| Přispěvatelé: | Kurkova, V, Manolopoulos, Y, Hammer, B, Iliadis, L, Maglogiannis, I, Informatics and Applied Informatics |
| Rok vydání: | 2018 |
| Předmět: |
Artificial neural network
Computer science business.industry Deep learning Feature vector Weather forecasting 02 engineering and technology Machine learning computer.software_genre Least squares Weighting Term (time) Support vector machine 03 medical and health sciences 0302 clinical medicine 13. Climate action 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer 030217 neurology & neurosurgery |
| Zdroj: | Artificial Neural Networks and Machine Learning – ICANN 2018 ISBN: 9783030014230 ICANN (3) Lecture Notes in Computer Science Lecture Notes in Computer Science-Artificial Neural Networks and Machine Learning – ICANN 2018 Artificial Neural Networks and Machine Learning – ICANN 2018-27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III Vrije Universiteit Brussel |
| ISSN: | 0302-9743 1611-3349 |
| Popis: | © Springer Nature Switzerland AG 2018. In multi-view regression the information from multiple representations of the input data is combined to improve the prediction. Inspired by the success of deep learning, this paper proposes a novel model called Weighted Multi-view Deep Neural Networks (MV-DNN) regression. The objective function used is a weighted version of the primal formulation of the existing Multi-View Least Squares Support Vector Machines method, where both the objectives from all different views, as well as the coupling term, are weighted. This work is motivated by the challenging application of weather forecasting. To predict the temperature, the weather variables from several previous days are taken into account. Each feature vector belonging to a previous day (delay) is regarded as a different view. Experimental results on the minimum and maximum temperature prediction in Brussels, reveal the merit of the weighting and show promising results when compared to existing the state-of-the-art methods in weather prediction. ispartof: pages:489-499 ispartof: ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2018, PT III vol:11141 pages:489-499 ispartof: International Conference on Artificial Neural Networks 2018 (ICANN 2018) location:Rhodes, Greece date:4 Oct - 7 Oct 2018 status: published |
| Databáze: | OpenAIRE |
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