About: Mining Linguistic Associations for Emergent Flood Prediction Adjustment

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Floods belong to the most hazardous natural disasters and their disaster management heavily relies on precise forecasts of water flow rates. These forecasts are provided by sophisticated physical models based on differential equations. However, these models do depend on unreliable inputs. Thus, an appropriate data-mining analysis of the physical model and its precision based on features that determine distinct situations seems to be helpful in adjusting the physical model. An of application of fuzzy GUHA method in flood peak prediction is presented in this paper. Measured water flow rate data from a system for emergent flood predictions were used in order to mine fuzzy association rules expressed in natural language. The found associations were interpreted as fuzzy IF-THEN rules and used to predict expected time shift of flow rate peaks forecasted by the given physical model. Floods belong to the most hazardous natural disasters and their disaster management heavily relies on precise forecasts of water flow rates. These forecasts are provided by sophisticated physical models based on differential equations. However, these models do depend on unreliable inputs. Thus, an appropriate data-mining analysis of the physical model and its precision based on features that determine distinct situations seems to be helpful in adjusting the physical model. An of application of fuzzy GUHA method in flood peak prediction is presented in this paper. Measured water flow rate data from a system for emergent flood predictions were used in order to mine fuzzy association rules expressed in natural language. The found associations were interpreted as fuzzy IF-THEN rules and used to predict expected time shift of flow rate peaks forecasted by the given physical model. (en)
Title	Mining Linguistic Associations for Emergent Flood Prediction Adjustment Mining Linguistic Associations for Emergent Flood Prediction Adjustment (en)
skos:prefLabel	Mining Linguistic Associations for Emergent Flood Prediction Adjustment Mining Linguistic Associations for Emergent Flood Prediction Adjustment (en)
skos:notation	RIV/61988987:17610/13:A14018JV!RIV14-MSM-17610___
http://linked.open...avai/predkladatel	Centrum excelence IT4Innovations, divize OU, Ústav pro výzkum a aplikace fuzzy modelování
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(ED1.1.00/02.0070), S
http://linked.open...iv/cisloPeriodika	1
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Rusnok, Pavel Burda, Michal Štěpnička, Martin
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ostravská univerzita v Ostravě / Centrum excelence IT4Innovations, divize OU, Ústav pro výzkum a aplikace fuzzy modelování
http://linked.open...dnocenehoVysledku	88486
http://linked.open...ai/riv/idVysledku	RIV/61988987:17610/13:A14018JV
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	GUHA; fuzzy rules; floods; perception-based logical deduction (en)
http://linked.open.../riv/klicoveSlovo	fuzzy rules GUHA perception-based logical deduction floods
http://linked.open...odStatuVydavatele	US - Spojené státy americké
http://linked.open...ontrolniKodProRIV	[9F93F1A8960E]
http://linked.open...i/riv/nazevZdroje	Advances in Fuzzy Systems
http://linked.open...in/vavai/riv/obor	BA
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	IT4Innovations Centre of Excellence
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	2013
http://linked.open...iv/tvurceVysledku	Štěpnička, Martin Burda, Michal Rusnok, Pavel
issn	1687-7101
number of pages	10 (xsd:int)
http://localhost/t...ganizacniJednotka	17610

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