A neural network model for short term prediction of surface ozone at Pone

Authors

  • P. GUHATHAKURTA

DOI:

https://doi.org/10.54302/mausam.v50i1.1809

Keywords:

Air Pollution, Neural network, Surface ozone, Short term prediction

Abstract

A new method for short term prediction of air pollution is presented using the neural network technique, Due to increase in industrial and anthropogenic activity, air pollution is a serious subject of concern today, Surface ozone can be considered as a representative of total atmospheric oxidants and of air pollution, A three layer neural network model using the technique of adaptive pattern recognition is developed, The model can predict the mean surface ozone between 12 and 13 hours (hour of maximum concentration), The model can perform well both in training and independent periods, The classical methods of short term modelling are not reliable enough, The method can also be used for short term prediction of other air pollutants.

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Published

01-01-1999

How to Cite

[1]
P. . GUHATHAKURTA, “A neural network model for short term prediction of surface ozone at Pone”, MAUSAM, vol. 50, no. 1, pp. 91–98, Jan. 1999.

Issue

Vol. 50 No. 1 (1999): MAUSAM

Section

Research Papers

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