Analysis and prediction of air quality data with the gamma classifier

Cornelio Yáñez-Márquez, Itzamá López-Yáñez, Guadalupe DeLaLuzSáenzMorales

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

In later years, different environmental phenomena have attracted the attention of artificial intelligence and machine learning researchers. In particular, several research groups have applied genetic algorithms and artificial neural networks to the analysis of data related to atmospheric and environmental sciences. In the current work, the results of applying the Gamma classifier to the analysis and prediction of air quality data related to the Mexico City Air Quality Metropolitan Index (IMECA in Spanish) are presented. © 2008 Springer-Verlag Berlin Heidelberg.
Original languageAmerican English
Title of host publicationAnalysis and prediction of air quality data with the gamma classifier
Pages651-658
Number of pages585
ISBN (Electronic)3540859195, 9783540859192
DOIs
StatePublished - 10 Nov 2008
Externally publishedYes
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2014 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5197 LNCS
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/14 → …

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Yáñez-Márquez, C., López-Yáñez, I., & DeLaLuzSáenzMorales, G. (2008). Analysis and prediction of air quality data with the gamma classifier. In Analysis and prediction of air quality data with the gamma classifier (pp. 651-658). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5197 LNCS). https://doi.org/10.1007/978-3-540-85920-8_79