intelligent database systems lab n.y.u.s.t. i. m. comparison of neural network models with arima and...

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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 國國國國國國國國 National Yunlin University of Science and Technology

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Page 1: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.

Comparison of neural network models with ARIMA andregression 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

Page 2: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Outline

Motivation Objective Methodology Experiments Conclusion Comments

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Page 3: 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

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.

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Page 4: 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

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.

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Max

Ozone

ARIMA

NN

Regression

Page 5: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology

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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

Page 6: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology

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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)

Page 7: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology

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ARIMA (p, d, q) model building Autoregressive Integrated Moving Average ARIMA(1,0,0)

Simpson and Layton (1983)Daily maximum ozone level

Page 8: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

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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)

Page 9: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

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NN ARIMA Regression

MAD 0.012945 0.02879 0.025741

RMS 0.016418 0.033023 0.031239

Page 10: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Conclusion

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The results show that the neural network model is superior to the regression and ARIMA models.

NN ARIMA Regression

MAD 0.012945 0.02879 0.025741

RMS 0.016418 0.033023 0.031239

Page 11: 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

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Comments

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Advantage This paper is easy to read.

Drawback This paper lack more experiments.

Application It is possible to predict the time series data.