Statistical modeling for the prediction of ozone concentrations in the dallas-forth worth area

Chivalai Temiyasathit, Seoung Bum Kim, Neelesh V. Sule

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

Vast amounts of data are being generated to extract implicit patterns of ambient air pollutants. This study attempts to investigate the behavior of daily maximum 8-hour ozone concentrations measured at 15 monitoring sites in the Dallas-Fort Worth area from June 1, 2002 to May 31, 2006. Time-series models were constructed to predict ozone concentrations. Regression trees were developed to study how meteorological variables impact ozone concentrations. The diagnostic test demonstrated the accurate predictability of the constructed time-series model. Further, regression trees identified important variables to predict ozone concentrations.

Original languageEnglish
Pages670-675
Number of pages6
Publication statusPublished - 2007
EventIIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World - Nashville, TN, United States
Duration: 2007 May 192007 May 23

Other

OtherIIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World
CountryUnited States
CityNashville, TN
Period07/5/1907/5/23

Keywords

  • Ozone prediction
  • Time series analysis
  • Tree-based model

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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    Temiyasathit, C., Kim, S. B., & Sule, N. V. (2007). Statistical modeling for the prediction of ozone concentrations in the dallas-forth worth area. 670-675. Paper presented at IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World, Nashville, TN, United States.