Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations
- 1 April 2000
- journal article
- Published by Elsevier in European Journal of Operational Research
- Vol. 122 (1), 31-40
- https://doi.org/10.1016/s0377-2217(99)00069-7
Abstract
No abstract availableKeywords
This publication has 18 references indexed in Scilit:
- Wheat-kernel growth characteristics during exposure to chronic ozone pollutionEnvironmental Pollution, 1993
- Simulation of polysaccharide carbon-13 nuclear magnetic resonance spectra using regression analysis and neural networksAnalytical Chemistry, 1993
- Ozone in the urban southeastern United StatesEnvironmental Pollution, 1992
- An Air Quality Data Analysis System for Interrelating Effects, Standards, and Needed Source Reductions: Part 8. An Effective Mean O3Crop Reduction Mathematical ModelJournal of the Air Pollution Control Association, 1984
- Forecasting peak ozone levelsAtmospheric Environment (1967), 1983
- Approach to forecasting daily maximum ozone levels in St. LouisEnvironmental Science & Technology, 1981
- An Empirical Model for Forecasting Maximum Daily Ozone Levels in the Northeastern U.S.Journal of the Air Pollution Control Association, 1978
- Ozone Forecasting Using Empirical ModelingJournal of the Air Pollution Control Association, 1978
- Time-series analysis of Riverside, California air quality dataAtmospheric Environment (1967), 1975
- Linear stochastic models for forecasting daily maxima and hourly concentrations of air pollutantsAtmospheric Environment (1967), 1975