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A Hybrid Regression System Based on Local Models for Solar Energy Prediction
Volume 25, Issue 2 (2014), pp. 265–282
Héctor Quintián   Jose Luis Calvo-Rolle   Emilio Corchado  

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https://doi.org/10.15388/Informatica.2014.14
Pub. online: 1 January 2014      Type: Research Article     

Received
1 April 2012
Accepted
1 September 2013
Published
1 January 2014

Abstract

The aim of this study is to predict the energy generated by a solar thermal system. To achieve this, a hybrid intelligent system was developed based on local regression models with low complexity and high accuracy. Input data is divided into clusters by using a Self Organization Maps; a local model will then be created for each cluster. Different regression techniques were tested and the best one was chosen. The novel hybrid regression system based on local models is empirically verified with a real dataset obtained by the solar thermal system of a bioclimatic house.

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Keywords
hybrid system clustering local models SOM MLP SVM prediction solar energy

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INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
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