A neural net-air dispersion model validation study using the Indianapolis urban data set
by A. Pelliccioni, C. Gariazzo, T. Tirabassi
International Journal of Environment and Pollution (IJEP), Vol. 40, No. 1/2/3, 2010

Abstract: It is presented an integrated model composed by a dispersion model and a Neural Net (NN). The NN uses the concentrations predicted by the an analytical dispersion model as input variables of the net. This methodology was validated using Indianapolis urban data set where releases from an elevated emission source were considered. An improvement of performances is shown when the neural network is added downstream to the dispersion model. Tests reveal the system is able to reproduce the expected behaviour of pollutant concentration, with the downwind distance and stability of the atmosphere in urban area.

Online publication date: Mon, 11-Jan-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Environment and Pollution (IJEP):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com