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 contributionpeer-review

14 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.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings
Pages651-658
Number of pages8
DOIs
StatePublished - 2008
Event13th Iberoamerican Congress on Pattern Recognition, CIARP 2008 - Havana, Cuba
Duration: 9 Sep 200812 Sep 2008

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
ISSN (Electronic)1611-3349

Conference

Conference13th Iberoamerican Congress on Pattern Recognition, CIARP 2008
Country/TerritoryCuba
CityHavana
Period9/09/0812/09/08

Keywords

  • Air quality forecast
  • Gamma classifier

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