Mining Linguistic Associations for Emergent Flood Prediction Adjustment
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F13%3AA14018JV" target="_blank" >RIV/61988987:17610/13:A14018JV - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Mining Linguistic Associations for Emergent Flood Prediction Adjustment
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Mining Linguistic Associations for Emergent Flood Prediction Adjustment
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
BA - Obecná matematika
OECD FORD obor
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Návaznosti výsledku
Projekt
<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2013
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Advances in Fuzzy Systems
ISSN
1687-7101
e-ISSN
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Svazek periodika
2013
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
10
Strana od-do
1-10
Kód UT WoS článku
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EID výsledku v databázi Scopus
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