NEURAL NETWORK PREDICTION OF MONTHLY PRECIPITATION: APPLICATION TO SUMMER FLOOD OCCURRENCE IN TWO REGIONS OF CENTRAL EUROPE

dc.contributor.authorBodri L.
dc.contributor.authorCermak V.
dc.date.accessioned2021-03-19T05:26:31Z
dc.date.available2021-03-19T05:26:31Z
dc.date.issued2001
dc.description.abstractArtificial Neural Network (ANN) models were used to forecast precipitation. Three-layer back propagation ANNs were trained with actual monthly precipitation data from six Czech and four Hungarian meteorological stations for the period 1961-1998. The predicted amounts are the next month's precipitation. Both training and testing ANN results provided a good fit with the actual data and displayed high feasibility in predicting extreme precipitation.
dc.identifierhttps://www.elibrary.ru/item.asp?id=1301129
dc.identifier.citationStudia Geophysica et Geodaetica, 2001, 45, 2, 155-167
dc.identifier.issn0039-3169
dc.identifier.urihttps://repository.geologyscience.ru/handle/123456789/26945
dc.subjectFLOOD
dc.subjectPRECIPITATION
dc.subjectNEURAL NETWORK
dc.subjectPREDICTION
dc.titleNEURAL NETWORK PREDICTION OF MONTHLY PRECIPITATION: APPLICATION TO SUMMER FLOOD OCCURRENCE IN TWO REGIONS OF CENTRAL EUROPE
dc.typeСтатья

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