[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: DM: ML in environment
Date: Tue, 20 Apr 1999 09:04:04 -0400 (EDT)
The kind of study that you are interested in involves the consideration of the saptio-temporal distribution of the data, i mean that the sampling process starting from the collection of the data to the prediction of the pollutants concentration should all be carried out keeping the particular distribution in mind. I hope, you would be looking for this while studying, and you can try out connecting to the site: http://curie.ei.jrc.it/software/index.htm and have got to download the GSLIB or GEOEAS or other packages and have a look ...You can get the relevant documentations : http://curie.ei.jrc.it/ai-geostats.htm
I hope this helps ... Regards: Debashish. email@example.com on 04/19/99 12:55:07 PM To: firstname.lastname@example.org cc: (bcc: Debashish Chakravarty/PWA) Subject: DM: ML in environmentHello,
I am a post-grad. student who tries to write an overview about the applications of Machine Learning in air-quality and air-pollution control problems.
I would be grateful if anyone of you could provide me with useful links to similar work done in the past. I know so far of efforts made with Neural Networks, and I wander if someone else has ever tried to do the same using Decision Trees, Bayesian modeling, evolutionary algorithms or some other algorithm.
[Usually what one wants to predict is the levels of some dangerous pollutant for the next 8 or 12 or 24 or even 48 hours]
------------------------------ ===== Elias Kalapanidas ====== == University of Patras == = Electric Engineering Dept = email@example.com