Neural networks fusion for temperature forecasting
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S.I. : ADVANCES IN BIO-INSPIRED INTELLIGENT SYSTEMS
Neural networks fusion for temperature forecasting Jose´ Gustavo Herna´ndez-Travieso1 Carlos M. Travieso-Gonza´lez3
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Antonio G. Ravelo-Garcı´a2
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Jesu´s B. Alonso-Herna´ndez3
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Received: 18 January 2018 / Accepted: 16 March 2018 The Natural Computing Applications Forum 2018
Abstract Weather conditions have a direct relationship with energy consumption, touristic activities, and farm tasks. By means of the fusion of artificial neural networks, this work presents a system with a general method that obtains an accurate temperature prediction. The objective is temperature, but the method is easily scalable to obtain any other meteorological parameter; this is one strength of the model. This research carries out a temperature prediction modeling that contributes to obtain better results with different applications as energy generation or in other different fields such as tourism or farming. The database contains data of 5 years from stations located in Gran Canaria at Gran Canaria Airport and in Tenerife at Tenerife Sur Airport. Data are collected hourly, what means more than 100,000 samples. This quantity of samples gives sturdiness to the study. With this method, our best result in terms of mean absolute error and using data from meteorological stations in Canary Islands is 0.41 C. Keywords Score fusion Modeling Temperature prediction Artificial neural networks
1 Introduction
& Jose´ Gustavo Herna´ndez-Travieso [email protected] Antonio G. Ravelo-Garcı´a [email protected] Jesu´s B. Alonso-Herna´ndez [email protected] Carlos M. Travieso-Gonza´lez [email protected] 1
Institute for Technological Development and Innovation in Communications (IDeTIC), University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017 Las Palmas de Gran Canaria, Spain
2
Signal and Communications Department, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, sn, Ed. de Telecomunicacio´n, Pabello´n B, 35017 Las Palmas de Gran Canaria, Spain
3
Signal and Communications Department, Institute for Technological Development and Innovation in Communications (IDeTIC), University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, sn, Ed. de Telecomunicacio´n, Pabello´n B, Despacho 111, 35017 Las Palmas de Gran Canaria, Spain
This work presents a novel method of fusion of artificial neural networks (ANN) in order to obtain a temperature forecasting. Using most voted method, this proposal can be applied to the improvement in energy generation process and to the increase in the use of renewable energy. Currently, sources like petroleum derived or carbon are the most used in the energy generation process [1], leading to an increase in temperature and greenhouse effect. In addition, efficiency in the generation process in Spain and Portugal in 2013 was only of 39.20% [2] using fossil fuels compared to 80% from hydraulic power [3], representing clearly the int
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