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

dc.contributor.author	Bodri L.
dc.contributor.author	Cermak V.
dc.date.accessioned	2021-03-19T05:26:31Z
dc.date.available	2021-03-19T05:26:31Z
dc.date.issued	2001
dc.identifier	https://www.elibrary.ru/item.asp?id=1301129
dc.identifier.citation	Studia Geophysica et Geodaetica, 2001, 45, 2, 155-167
dc.identifier.issn	0039-3169
dc.identifier.uri	https://repository.geologyscience.ru/handle/123456789/26945
dc.description.abstract	Artificial 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.subject	FLOOD
dc.subject	PRECIPITATION
dc.subject	NEURAL NETWORK
dc.subject	PREDICTION
dc.title	NEURAL NETWORK PREDICTION OF MONTHLY PRECIPITATION: APPLICATION TO SUMMER FLOOD OCCURRENCE IN TWO REGIONS OF CENTRAL EUROPE
dc.type	Статья

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