Comparison of artifical intelligence prediction techniques in NO and NO2 concentrations' forecast

Juhos, István and Béczi, Rita and Makra, László: Comparison of artifical intelligence prediction techniques in NO and NO2 concentrations' forecast. Acta climatologica, (36-37). pp. 45-55. (2003)

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To construct new technical devices, to permanently protect buildings and to reduce the expenses of various economic and business processes more and more accurate prediction techniques are needed. Almost all human activities encounter the hard problem of forecasting. Although several time series prediction methods have been developed, each of them has certain limitations. Most of them are designed rather for modeling complete time series than pointing out different prediction characteristics; furthermore, they can only be interpreted with difficulties. Artificial intelligence offers symbolic learning with decision trees, by means of which we can explore connections in past data and produce them in a readable format Decision trees can estimate intervals of future data. Recently, artificial neural networks were used to handle this problem. This method offered more precise forecast and more accurate fit of the function to the starting data. However, when applying this method, relationships in the data set examined were hidden. If we combine the methods mentioned above, we can get more precise decisions for the future data and we can also reveal the reasons. In either case, the efficiency of learning depends on a good choice of the learning algorithms' parameters. For this reason, parameters are selected by simulated annealing. The aim of this paper is to conpare die above mentioned prediction techniques in several hours forecast of NO and NO2 concentrations at a busy cross-road in Szeged (Hungary). For this object, meteorological parameters predicted with given error on their actual values were used.

Item Type: Article
Journal or Publication Title: Acta climatologica
Date: 2003
Volume: 36-37
Page Range: pp. 45-55
ISSN: 0563-0614
Language: angol
Uncontrolled Keywords: Földrajztudomány
Additional Information: Bibliogr.: 55.p.; Összefoglalás; Summary
Date Deposited: 2016. Oct. 15. 14:10
Last Modified: 2018. Jun. 04. 13:12

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