Linked Life Data

11379159

Source:http://linkedlifedata.com/resource/pubmed/id/11379159

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2001-5-29
pubmed:abstractText
There has been an increasing demand for accurate rainfall forecast in urban areas from the water industry. Current forecasting systems provided mainly by meteorological offices are based on large-scale prediction and are not well suited for this application. In order to devise a system especially designed for the dynamic management of a sewerage system the "RADAR" project was launched. The idea of this project was to provide a short-term small-scale prediction of rain based on radar images. The prediction methodology combines two methods. An extrapolation method based on a sophisticated cross correlation of images is optimised by a neural network technique. Three different application sites in Europe have been used to validate the system.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0273-1223
pubmed:author
pubmed:issnType
Print
pubmed:volume
43
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
79-86
pubmed:dateRevised
2006-4-19
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Radar based rainfall forecast for sewage systems control.
pubmed:affiliation
Malmö Water, S-205 80 Malmö, Sweden.
pubmed:publicationType
Journal Article