Prediction of CO and NOx Levels in Mexico City Using Associative Models

Abstract : Artificial Intelligence has been present since more than two decades ago, in the treatment of data concerning the protection of the environment; in particular, various groups of researchers have used genetic algorithms and artificial neural networks in the analysis of data related to the atmospheric sciences and the environment. However, in this kind of applications has been conspicuously absent from the associative models, by virtue of which the classic associative techniques exhibit very low yields. This article presents the results of applying Alpha-Beta associative models in the analysis and prediction of the levels of Carbon Monoxide (CO) and Nitrogen Oxides (NOx) in Mexico City.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.313-322, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_38〉
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Amadeo Argüelles, Cornelio Yáñez, Itzamá López, Oscar Camacho. Prediction of CO and NOx Levels in Mexico City Using Associative Models. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.313-322, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_38〉. 〈hal-01571491〉

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