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