About: Model of multilayer artificial neural network for prediction of iron ore demand

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	With regards to many effects which can disrupt the delivery schedule of iron ore to a company, this raw material must be ordered well in advance. Determination of the required order volume results from prediction of iron ore demand. With respect to the fluctuations on the metallurgical commodity market, it is very difficult to use classical prediction models based on time series analysis. A typical example when models based solely on historical time series can not be used to predict iron ore demand is the world economic crisis period, because the demand for metallurgical commodities witnesses a sharp decrease. The article presents prediction model based on multilayer artificial neural network which takes into account not only historical data of iron ore demand but also information regarding the current situation on the world steel market and the iron ore stock volume of a given metallurgical company. The model is designed in such a way that the output is represented by the demand prediction of iron ore for the next month. Levenberg-Maguardt algorithm was used for learning the network. The proposed model should be included in the hybrid intelligent decision support system which will make it possible to efficiently reduce uncertainty and risk of logistics decision-making in the sphere of iron ore supply. With regards to many effects which can disrupt the delivery schedule of iron ore to a company, this raw material must be ordered well in advance. Determination of the required order volume results from prediction of iron ore demand. With respect to the fluctuations on the metallurgical commodity market, it is very difficult to use classical prediction models based on time series analysis. A typical example when models based solely on historical time series can not be used to predict iron ore demand is the world economic crisis period, because the demand for metallurgical commodities witnesses a sharp decrease. The article presents prediction model based on multilayer artificial neural network which takes into account not only historical data of iron ore demand but also information regarding the current situation on the world steel market and the iron ore stock volume of a given metallurgical company. The model is designed in such a way that the output is represented by the demand prediction of iron ore for the next month. Levenberg-Maguardt algorithm was used for learning the network. The proposed model should be included in the hybrid intelligent decision support system which will make it possible to efficiently reduce uncertainty and risk of logistics decision-making in the sphere of iron ore supply. (en)
Title	Model of multilayer artificial neural network for prediction of iron ore demand Model of multilayer artificial neural network for prediction of iron ore demand (en)
skos:prefLabel	Model of multilayer artificial neural network for prediction of iron ore demand Model of multilayer artificial neural network for prediction of iron ore demand (en)
skos:notation	RIV/61989100:27360/11:86081883!RIV12-MSM-27360___
http://linked.open...avai/riv/aktivita	S Z
http://linked.open...avai/riv/aktivity	S, Z(MSM6198910015)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Besta, Petr Lenort, Radim
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / Fakulta metalurgie a materiálového inženýrství
http://linked.open...dnocenehoVysledku	212897
http://linked.open...ai/riv/idVysledku	RIV/61989100:27360/11:86081883
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	artificial neural network; iron ore demand; prediction models (en)
http://linked.open.../riv/klicoveSlovo	prediction models artificial neural network iron ore demand
http://linked.open...ontrolniKodProRIV	[5F1EA6ED6F47]
http://linked.open...v/mistoKonaniAkce	Brno
http://linked.open...i/riv/mistoVydani	Ostrava
http://linked.open...i/riv/nazevZdroje	20th Anniversary International Conference on Metallurgy and Materials: METAL 2011
http://linked.open...in/vavai/riv/obor	AE
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...UplatneniVysledku	2011
http://linked.open...iv/tvurceVysledku	Besta, Petr Lenort, Radim Feliks, J.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-05-18 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Structural potentiality and properties of intensively formed materials
number of pages	5 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Tanger s.r.o.
https://schema.org/isbn	978-80-87294-24-6
http://localhost/t...ganizacniJednotka	27360

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