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A Support Vector Regression Approach to Predict Carbon Dioxide Exchange: Profile on PlumX
Título : A Support Vector Regression Approach to Predict Carbon Dioxide Exchange
Autor(es) : de Paz Santana, Juan F.
Pérez, Belén
González Arrieta, Angélica
Corchado Rodríguez, Emilio
Corchado Rodríguez, Juan M.
Palabras clave : Computer Science
Fecha de publicación : 2010
Editor : Springer Science + Business Media
Citación : Distributed Computing and Artificial Intelligence Advances in Intelligent and Soft Computing. Advances in Intelligent and Soft Computing. Volumen 79, pp. 157-164.
Resumen : In this study, a new monitoring system for carbon dioxide exchange is presented. The mission of the intelligent environment presented in this work, is to globally monitor the interaction between the ocean’s surface and the atmosphere, facilitating the work of oceanographers. This paper proposes a hybrid intelligent system integrates case-based reasoning (CBR) and support vector regression (SVR) characterised for their efficiency for data processing and knowledge extraction. Results have demonstrated that the system accurately predicts the evolution of the carbon dioxide exchange.
URI : http://hdl.handle.net/10366/134918
ISBN : 978-3-642-14882-8 (Print) / 978-3-642-14883-5 (Online)
ISSN : 1867-5662 (Print) / 1867-5670 (Online)
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