Intelligent Database Systems Lab N.Y.U.S.T. I. M. Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations Presenter: Jun-Yi Wu Authors: Victor R. Prybutok, Junsub Yi, David Mitchell 2000 ORMS 國立雲林科技大學 National Yunlin University of Science and Technology

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Outline Motivation Objective Methodology Experiments Conclusion Comments 2

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Motivation The Houston area has been designated a non-attainment area. This area started a campaign called “ Ozone Alert Day” It is difficult to predict the daily ozone concentration. 3

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objective To develop and compare a NN model for forecasting maximum daily ozone levels in a non-attainment area to regression and ARIMA models. 4 Max Ozone ARIMANNRegression

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 5 NN model building Dummy variable Ozone level at 9:00 Maximum daily temperature Carbon dioxide Nitric oxide Nitrogen dioxide Oxide of nitrogen Surface wind speed Surface wind direction Daily maximum ozone level (hourly average) BPLMS

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 6 Regression model building The preliminary regression model The stepwise procedure The final regression model Dummy variable Ozone level at 9:00 Maximum daily temperature Carbon dioxide Nitric oxide Nitrogen dioxide Oxide of nitrogen Surface wind speed Surface wind direction Daily maximum ozone level (hourly average)

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 7 ARIMA (p, d, q) model building Autoregressive Integrated Moving Average ARIMA(1,0,0) Simpson and Layton (1983) Daily maximum ozone level

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 8 Data collection 1 June -30 September (Train) October 1-10 (Test) Variable specification Dummy variable Ozone level at 9:00 Maximum daily temperature Carbon dioxide Nitric oxide Nitrogen dioxide Oxide of nitrogen Surface wind speed Surface wind direction Daily maximum ozone level (hourly average)

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 9 NNARIMARegression MAD RMS

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Conclusion 10 The results show that the neural network model is superior to the regression and ARIMA models. NNARIMARegression MAD RMS

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Comments 11 Advantage  This paper is easy to read. Drawback  This paper lack more experiments. Application  It is possible to predict the time series data.