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

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  • Prybutok, Victor R.
  • Yi, Junsub
  • Mitchell, David

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  • Prybutok, Victor R. & Yi, Junsub & Mitchell, David, 2000. "Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations," European Journal of Operational Research, Elsevier, vol. 122(1), pages 31-40, April.
    • Handle: RePEc:eee:ejores:v:122:y:2000:i:1:p:31-40
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    References listed on IDEAS

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    1. Hill, Tim & Marquez, Leorey & O'Connor, Marcus & Remus, William, 1994. "Artificial neural network models for forecasting and decision making," International Journal of Forecasting, Elsevier, vol. 10(1), pages 5-15, June.
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    Cited by:

    1. Koutroumanidis, Theodoros & Ioannou, Konstantinos & Arabatzis, Garyfallos, 2009. "Predicting fuelwood prices in Greece with the use of ARIMA models, artificial neural networks and a hybrid ARIMA-ANN model," Energy Policy, Elsevier, vol. 37(9), pages 3627-3634, September.
    2. Sotirios Bersimis & Stavros Degiannakis & Dimitrios Georgakellos, 2017. "Real-time monitoring of carbon monoxide using value-at-risk measure and control charting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 89-108, January.
    3. Florin Dan PIELEANU, 2016. "Comparative Study In Estimating Volkswagen’S Price: Arima Versus Ann," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(2), pages 98-109, February.
    4. Wang, Tai-Yue & Huang, Chien-Yu, 2007. "Improving forecasting performance by employing the Taguchi method," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1052-1065, January.
    5. Dong-jun Liu & Li Li, 2015. "Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM 2.5 Concentration in Guangzhou, China," IJERPH, MDPI, vol. 12(6), pages 1-15, June.
    6. Chu, Ching-Wu & Zhang, Guoqiang Peter, 2003. "A comparative study of linear and nonlinear models for aggregate retail sales forecasting," International Journal of Production Economics, Elsevier, vol. 86(3), pages 217-231, December.
    7. Zhao, Yuan & Zhang, Weiguo & Gong, Xue & Wang, Chao, 2021. "A novel method for online real-time forecasting of crude oil price," Applied Energy, Elsevier, vol. 303(C).
    8. Florin Dan Pieleanu, 2016. "Predicting The Evolution Of Bet Index, Using An Arima Model," Romanian Economic Business Review, Romanian-American University, vol. 10(1), pages 151-162, May.
    9. Marques, Alex & Lacerda, Daniel Pacheco & Camargo, Luís Felipe Riehs & Teixeira, Rafael, 2014. "Exploring the relationship between marketing and operations: Neural network analysis of marketing decision impacts on delivery performance," International Journal of Production Economics, Elsevier, vol. 153(C), pages 178-190.

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