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Artificial neural networks aided annual rainfall erosivity factor values calculation in Poland

dc.contributor.authorLicznar, Pawel
dc.contributor.editorWenkel, K.-O.
dc.contributor.editorWagner, P.
dc.contributor.editorMorgenstern, M.
dc.contributor.editorLuzi, K.
dc.contributor.editorEisermann, P.
dc.date.accessioned2019-08-26T09:34:34Z
dc.date.available2019-08-26T09:34:34Z
dc.date.issued2006
dc.description.abstractCalculation and analysis of annual R-factor local values for 103 stations in Poland were the main aims of this study. Calculations were made by means of single hidden layer perceptron artificial neural network on the base of monthly precipitation totals from years: 1961-1980. For most of the analyzed stations calculated average annual R-factor values were low or moderate, at the range from 50 to 80 MJ⋅ha-1⋅cm⋅h-1. A strong relation between calculated average annual factor values and station elevation above see level was observed. Because of this, geostatistical algorithms incorporating elevation information should be used for further updating the isoerodents map of Poland.en
dc.identifier.isbn3-88579-172-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/24703
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofLand- und Ernährungswirtschaft im Wandel – Aufgaben und Herausforderungen für die Agrar und Umweltinformatik
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-78
dc.titleArtificial neural networks aided annual rainfall erosivity factor values calculation in Polanden
dc.typeText/Conference Paper
gi.citation.endPage148
gi.citation.publisherPlaceBonn
gi.citation.startPage145
gi.conference.date06.-08. März 2006
gi.conference.locationPotsdam
gi.conference.sessiontitleRegular Research Papers

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