About: Artificial Intelligence Elements in Data Mining from Remote Experiments

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Artificial Intelligence Elements in Data Mining from Remote Experiments 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)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	In spite of the fact that remote laboratories have been existing for at least three decades, virtually no attention has been devoted to the accumulated data analysis of this new means of education. The paper deals with the data analysis, gathered in the Datacentre (DTC) implemented with the Laboratory Management System (RLMS), connected in turn to remote laboratories and re- mote experiments. In particular, we concentrate and describe a new model of experiment data analysis, based on the principles of artificial intelligence, based on the criterion function in need. The leading idea of the model functioning is during the procedure of rig(s) recognition i.e Data weighting: Data recognition: Data preparation: Phenomenon modelling: Model and measurement data com- parison: Result deployment, where the artificial intellingence is integrated with steps of Data weighting by association and regression using neuron network. Benefit of the suggested method is its speed and efficiency and thus using it for the optimization of individual remote experiments and ther efficiency. Paper may serve as an inspiring source for the development in the field of remote la- boratories, but it may influence in the similar areas of data mining. In spite of the fact that remote laboratories have been existing for at least three decades, virtually no attention has been devoted to the accumulated data analysis of this new means of education. The paper deals with the data analysis, gathered in the Datacentre (DTC) implemented with the Laboratory Management System (RLMS), connected in turn to remote laboratories and re- mote experiments. In particular, we concentrate and describe a new model of experiment data analysis, based on the principles of artificial intelligence, based on the criterion function in need. The leading idea of the model functioning is during the procedure of rig(s) recognition i.e Data weighting: Data recognition: Data preparation: Phenomenon modelling: Model and measurement data com- parison: Result deployment, where the artificial intellingence is integrated with steps of Data weighting by association and regression using neuron network. Benefit of the suggested method is its speed and efficiency and thus using it for the optimization of individual remote experiments and ther efficiency. Paper may serve as an inspiring source for the development in the field of remote la- boratories, but it may influence in the similar areas of data mining. (en)
Title	Artificial Intelligence Elements in Data Mining from Remote Experiments Artificial Intelligence Elements in Data Mining from Remote Experiments (en)
skos:prefLabel	Artificial Intelligence Elements in Data Mining from Remote Experiments Artificial Intelligence Elements in Data Mining from Remote Experiments (en)
skos:notation	RIV/61989100:27240/14:86093206!RIV15-MSM-27240___
http://linked.open...avai/riv/aktivita	S
http://linked.open...avai/riv/aktivity	S
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Zelinka, Ivan
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 elektrotechniky a informatiky
http://linked.open...dnocenehoVysledku	4150
http://linked.open...ai/riv/idVysledku	RIV/61989100:27240/14:86093206
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	ISES, analysis data, Measureserver, remote experiment, data mining (en)
http://linked.open.../riv/klicoveSlovo	data mining ISES remote experiment analysis data Measureserver
http://linked.open...ontrolniKodProRIV	[10B420ED392D]
http://linked.open...v/mistoKonaniAkce	Ostrava
http://linked.open...i/riv/mistoVydani	London
http://linked.open...i/riv/nazevZdroje	Nostradamus 2014: prediction, modeling and analysis of complex systems
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Zelinka, Ivan Pálka, Lukas Schauer, Franz
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2014-06-23 (xsd:date)
issn	2194-5357
number of pages	9 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-319-07400-9
http://localhost/t...ganizacniJednotka	27240

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

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, 48 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software