Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations

DOI10.1016/S0377-2217(99)00069-7zbMath0958.91056WikidataQ127472323 ScholiaQ127472323MaRDI QIDQ1971988

Yanyan Li

Publication date: 23 March 2000

Published in: European Journal of Operational Research (Search for Journal in Brave)

zbMATH Keywords

neural networksforecastingenvironmentregression

Mathematics Subject Classification ID

Stochastic network models in operations research (90B15) Neural networks for/in biological studies, artificial life and related topics (92B20) Environmental economics (natural resource models, harvesting, pollution, etc.) (91B76)

Related Items (3)

Improving forecasting performance by employing the Taguchi method ⋮ Real-time monitoring of carbon monoxide using value-at-risk measure and control charting ⋮ Nonlinear models for ground-level ozone forecasting

Cites Work

• Unnamed Item

This page was built for publication: Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations