Quantifying the Ocean's CO2 Budget with a CoHeL-IBR System

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. First steps have been taken towards this from an environmental and economic point of view, by using an instance based reasoning system, which incorporates a novel clustering and retrieval method - a Cooperative Maximum Likelihood Hebbian Learning model (CoHeL). This paper reviews the problems of measuring the ocean’s CO2 budget and presents the CoHeL model developed and outlines the IBR system developed to resolve the problem.

• Type: Conference
• Year: 2004
• Where: EWCBR
• Authors: Juan M. Corchado, Jim Aiken, Emilio Corchado, Nathalie Lefevre, Tim Smyth
• Keywords: Artificial Intelligence, CO2 Budget, EWCBR 2004, Global Co2 Budget, Ocean’s Co2 Budget