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Issue title: Binding Environmental Sciences and AI
Article type: Research Article
Authors: Corchado, Juan M.; | Aiken, Jim | Corchado, Emilio S. | Fdez-Riverola, Florentino
Affiliations: Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced s/n. 37008, Salamanca, Spain E-mail: corchado@usal.es | Centre for Air–Sea Interactions and fluxes (CASIX), Plymouth Marine Laboratory, Prospect Place, Plymouth, PL1 3 DH, UK E-mail: ja@pml.ac.uk | Departamento de Ingeniería Civil, Universidad de Burgos, C/ Francisco de Victoria s/n. 09006, Burgos, Spain E-mail: escorchado@ubu.es | Departamento de Informática, Universidad de Vigo, Campus Universitario As Lagoas s/n. 32004, Ourense, Spain E-mail: riverola@uvigo.es
Note: [] Corresponding author: Juan M. Corchado, Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced s/n. 37008, Salamanca, Spain.
Abstract: The interaction of the atmosphere and the ocean has a profound effect on climate, while the uptake by the oceans of a major fraction of atmospheric CO2 has a moderating influence. By improving accuracy in the quantification of the ocean's CO2 budget, a more precise estimation can be made of the terrestrial fraction of global CO2 budget and its subsequent effect on climate change. An instance-based reasoning system, which incorporates a novel neural-based clustering and retrieval method has been developed for estimating the CO2 budget. This paper reviews the problem of measuring the ocean's CO2 budget, presents the model developed to resolve it and presents the obtained results.
Keywords: CBR, instance-based reasoning system, Hebbian learning and clustering, application
Journal: AI Communications, vol. 18, no. 4, pp. 247-256, 2005
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