About: Forecasting the consumption of plates in plants producing heavy plate cut shapes     Goto   Sponge   NotDistinct   Permalink

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

AttributesValues
rdf:type
Description
  • The paper is focused on search for suitable prediction models used for medium-term forecasting of the consumption of plates in plants producing heavy plate cut shapes. Demand time series for five product families, from the point of view of steel grade, have been assorted for this purpose. The time series include monthly demand data for the period from January 2007 to December 2009. Firstly, quantitative techniques based on time series analysis were used for the forecasting: simple moving average model with a multiplicative seasonal adjustment, Winter's exponential smoothing model and seasonal autoregressive integrated moving average (SARIMA) model. However, the application of these models is connected with two problems. First, time series are disrupted by the world crisis impacts. Second, time series does not affect the cycle component. That is why a prediction model using multilayer artificial neural network has been created.
  • The paper is focused on search for suitable prediction models used for medium-term forecasting of the consumption of plates in plants producing heavy plate cut shapes. Demand time series for five product families, from the point of view of steel grade, have been assorted for this purpose. The time series include monthly demand data for the period from January 2007 to December 2009. Firstly, quantitative techniques based on time series analysis were used for the forecasting: simple moving average model with a multiplicative seasonal adjustment, Winter's exponential smoothing model and seasonal autoregressive integrated moving average (SARIMA) model. However, the application of these models is connected with two problems. First, time series are disrupted by the world crisis impacts. Second, time series does not affect the cycle component. That is why a prediction model using multilayer artificial neural network has been created. (en)
Title
  • Forecasting the consumption of plates in plants producing heavy plate cut shapes
  • Forecasting the consumption of plates in plants producing heavy plate cut shapes (en)
skos:prefLabel
  • Forecasting the consumption of plates in plants producing heavy plate cut shapes
  • Forecasting the consumption of plates in plants producing heavy plate cut shapes (en)
skos:notation
  • RIV/61989100:27360/10:86076813!RIV11-MSM-27360___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 259511
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27360/10:86076813
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • shapes; cut; plate; heavy; producing; plants; plates; consumption; Forecasting (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [FA7CC8CF9939]
http://linked.open...v/mistoKonaniAkce
  • Rožnov pod Radhoštěm
http://linked.open...i/riv/mistoVydani
  • Rožnov pod Radhoštěm
http://linked.open...i/riv/nazevZdroje
  • METAL 2010
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Lenort, Radim
  • Feliks, J.
  • Staš, David
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • TANGER s.r.o. Ostrava
https://schema.org/isbn
  • 978-80-87294-17-8
http://localhost/t...ganizacniJednotka
  • 27360
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 36 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software