About: Utilization of Artificial Neuron Networks to Predict Leaking Firedamps from Underground

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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	This monograph is focused on designing and realizing an underlying area model using artificial neural networks. A method of artificial neural networks to create a model of underlying rocks was chosen in default of extract information on the underlying rock structure at risk areas. The main objective of this model is to predict firedamp leakage from underground, based on data measured at the surface of the risk area. This makes it possible to create very accurate prediction system that can be used for effective management of hazardous mine gas extraction and thereby ensure better protection of persons and property. The monograph describes in detail the used method of neural networks and also briefly describes other methods that were used in the modeling of this issue. However, these methods are applicable only to very limited cases and it is reason why only the method utilization of artificial neural networks is described in detail. This monograph is focused on designing and realizing an underlying area model using artificial neural networks. A method of artificial neural networks to create a model of underlying rocks was chosen in default of extract information on the underlying rock structure at risk areas. The main objective of this model is to predict firedamp leakage from underground, based on data measured at the surface of the risk area. This makes it possible to create very accurate prediction system that can be used for effective management of hazardous mine gas extraction and thereby ensure better protection of persons and property. The monograph describes in detail the used method of neural networks and also briefly describes other methods that were used in the modeling of this issue. However, these methods are applicable only to very limited cases and it is reason why only the method utilization of artificial neural networks is described in detail. (en)
Title	Utilization of Artificial Neuron Networks to Predict Leaking Firedamps from Underground Utilization of Artificial Neuron Networks to Predict Leaking Firedamps from Underground (en)
skos:prefLabel	Utilization of Artificial Neuron Networks to Predict Leaking Firedamps from Underground Utilization of Artificial Neuron Networks to Predict Leaking Firedamps from Underground (en)
skos:notation	RIV/61989100:27350/14:86091842!RIV15-MSM-27350___
http://linked.open...avai/riv/aktivita	I
http://linked.open...avai/riv/aktivity	I
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Řepka, Michal
http://linked.open.../riv/druhVysledku	B - Odborná kniha
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 / Hornicko-geologická fakulta
http://linked.open...dnocenehoVysledku	52600
http://linked.open...ai/riv/idVysledku	RIV/61989100:27350/14:86091842
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Methane Prediction; Back Propagation; Perceptron; Neural networks (en)
http://linked.open.../riv/klicoveSlovo	Back Propagation Neural networks Perceptron Methane Prediction
http://linked.open...ontrolniKodProRIV	[956809B42CD6]
http://linked.open...i/riv/mistoVydani	Košice
http://linked.open...vEdiceCisloSvazku	first, Košice 2014
http://linked.open...i/riv/nazevZdroje	Utilization of Artificial Neuron Networks to Predict Leaking Firedamps from Underground
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...v/pocetStranKnihy	104 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Řepka, Michal
number of pages	104 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Technická univerzita v Košiciach, Slovakia
https://schema.org/isbn	978-80-553-1842-4
http://localhost/t...ganizacniJednotka	27350

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