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Artificial neural network prediction of ground-level ozone concentration in Palm Beach County

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Date Issued:
1999
Summary:
The purpose of this study was to develop a user-friendly mathematical model for prediction of daily, ground level ozone concentration in Palm Beach County, Florida. The focus of this project was to investigate the correlation between hourly ozone concentrations and pre-existing pollutant levels and meteorological data. An artificial neural network model was applied, involving a backpropagation algorithm and the tangent sigmoid as the transfer function. Surface meteorological data and upper air data such as pressure, temperature, dew point temperature, wind speed and wind direction were included in the model, along with the ozone concentration in the hour previous to the forecast. Based on the model results, the 8-hour average ozone concentration is to be forecasted. This will assist state and local air pollution officials in providing the general public with early notice of an impending air quality problem.
Title: Artificial neural network prediction of ground-level ozone concentration in Palm Beach County.
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Name(s): Crumiere, Mylene.
Florida Atlantic University, Degree grantor
Scarlatos, Panagiotis (Pete) D., Thesis advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1999
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 96 p.
Language(s): English
Summary: The purpose of this study was to develop a user-friendly mathematical model for prediction of daily, ground level ozone concentration in Palm Beach County, Florida. The focus of this project was to investigate the correlation between hourly ozone concentrations and pre-existing pollutant levels and meteorological data. An artificial neural network model was applied, involving a backpropagation algorithm and the tangent sigmoid as the transfer function. Surface meteorological data and upper air data such as pressure, temperature, dew point temperature, wind speed and wind direction were included in the model, along with the ozone concentration in the hour previous to the forecast. Based on the model results, the 8-hour average ozone concentration is to be forecasted. This will assist state and local air pollution officials in providing the general public with early notice of an impending air quality problem.
Identifier: 9780599540521 (isbn), 15723 (digitool), FADT15723 (IID), fau:12479 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 1999.
Subject(s): Neural networks (Computer science)
Air--Pollution--Mathematical models
Air--Pollution--Florida--Palm Beach County
Ozone--Forecasting
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/15723
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.