000			02180naa a2200289 a 4500
003			AR-LpUFIB
005			20250311170423.0
008			230201s2014 xx o 000 0 eng d
024	8		_aDIF-M6763 _b6900 _zDIF006171
040			_aAR-LpUFIB _bspa _cAR-LpUFIB
100	1		_aGaudiani, Adriana Angélica
245	1	0	_aComputing, a powerful tool for improving the parameters simulation quality in flood prediction
300			_a1 archivo (2,5 MB)
500			_aFormato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
520			_aFloods have caused widespread damage throughout the world. Modelling and simulation pro- vide solutions and tools which enable us to forecast and make necessary steps toward prevention. One problem that must be handled by physical systems simulators is the parameters uncer- tainty and their impact on output results, causing prediction errors. In this paper, we address input parameter uncertainty toward providing a methodology to tune a flood simulator and achieve lower error between simulated and observed results. The tuning methodology, through a parametric simulation technique, implements a first stage to find an adjusted set of critical parameters which will be used to validate the predictive capability of the simulator in order to reduce the disagreement between observed data and simulated results. We concentrate our experiments in three significant monitoring stations, located at the lower basin of the Paran ́ a River in Argentina, and the percentage of improvement over the original simulator values ranges from 33 to 60%.
534			_aInternational Conference on Computational Science.(14º : 2014 : Guimaraes, Portugal) Reino Unido, Elsevier, 2014. (Procedia Computer Science, 29), pp. 299-309.
650		4	_aSIMULACIÓN
650		4	_aCOMPUTACIÓN DE ALTO RENDIMIENTO - HPC
653			_a1
700	1		_aLuque, Emilio
700	1		_aGarcía, Pablo S.
700	1		_aRe, Mariano
700	1		_aNaiouf, Ricardo Marcelo
700	1		_aDe Giusti, Armando Eduardo
856	4	0	_uhtp://dx.doi.org/10.1016/j.procs.2014.05.027
942			_cCP
999			_c55953 _d55953