Agile Tuning Method in Successive Steps for a River Flow Simulator
- Autores
- Trigila, Mariano; Gaudiani, Adriana Angélica; Luque Fadón, Emilio
- Año de publicación
- 2018
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Scientists and engineers continuously build models to interpret axiomatic theories or explain the reality of the universe of interest to reduce the gap between formal theory and observation in practice. We focus our work on dealing with the uncertainty of the input data of the model to improve the quality of the simulation. To reduce this error, scientist and engineering implement techniques for model tuning and they look for ways to reduce their high computational cost. This article proposes a methodology for adjusting a simulator of a complex dynamic system that models the wave translation along rivers channels, with emphasis on the reduction of computation resources. We propose a simulator calibration by using a methodology based on successive adjustment steps of the model. We based our process in a parametric simulation. The input scenarios used to run the simulator at every step were obtained in an agile way, achieving a model improvement up to 50% in the reduction of the simulated data error. These results encouraged us to extend the adjustment process over a larger domain region.
Trabajo publicado en Lecture Notes in Computer Science book series (LNCS, vol. 10862)
Facultad de Informática - Materia
-
Ciencias Informáticas
Parametric simulation
tuning methodology
flood simulation improvement
dynamical systems
flood model calibration - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/127483
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Agile Tuning Method in Successive Steps for a River Flow SimulatorTrigila, MarianoGaudiani, Adriana AngélicaLuque Fadón, EmilioCiencias InformáticasParametric simulationtuning methodologyflood simulation improvementdynamical systemsflood model calibrationScientists and engineers continuously build models to interpret axiomatic theories or explain the reality of the universe of interest to reduce the gap between formal theory and observation in practice. We focus our work on dealing with the uncertainty of the input data of the model to improve the quality of the simulation. To reduce this error, scientist and engineering implement techniques for model tuning and they look for ways to reduce their high computational cost. This article proposes a methodology for adjusting a simulator of a complex dynamic system that models the wave translation along rivers channels, with emphasis on the reduction of computation resources. We propose a simulator calibration by using a methodology based on successive adjustment steps of the model. We based our process in a parametric simulation. The input scenarios used to run the simulator at every step were obtained in an agile way, achieving a model improvement up to 50% in the reduction of the simulated data error. These results encouraged us to extend the adjustment process over a larger domain region.Trabajo publicado en <i>Lecture Notes in Computer Science</i> book series (LNCS, vol. 10862)Facultad de Informática2018info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf639-646http://sedici.unlp.edu.ar/handle/10915/127483enginfo:eu-repo/semantics/altIdentifier/issn/0302-9743info:eu-repo/semantics/altIdentifier/issn/1611-3349info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-93713-7_60info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:30:43Zoai:sedici.unlp.edu.ar:10915/127483Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:30:43.961SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Agile Tuning Method in Successive Steps for a River Flow Simulator |
title |
Agile Tuning Method in Successive Steps for a River Flow Simulator |
spellingShingle |
Agile Tuning Method in Successive Steps for a River Flow Simulator Trigila, Mariano Ciencias Informáticas Parametric simulation tuning methodology flood simulation improvement dynamical systems flood model calibration |
title_short |
Agile Tuning Method in Successive Steps for a River Flow Simulator |
title_full |
Agile Tuning Method in Successive Steps for a River Flow Simulator |
title_fullStr |
Agile Tuning Method in Successive Steps for a River Flow Simulator |
title_full_unstemmed |
Agile Tuning Method in Successive Steps for a River Flow Simulator |
title_sort |
Agile Tuning Method in Successive Steps for a River Flow Simulator |
dc.creator.none.fl_str_mv |
Trigila, Mariano Gaudiani, Adriana Angélica Luque Fadón, Emilio |
author |
Trigila, Mariano |
author_facet |
Trigila, Mariano Gaudiani, Adriana Angélica Luque Fadón, Emilio |
author_role |
author |
author2 |
Gaudiani, Adriana Angélica Luque Fadón, Emilio |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Parametric simulation tuning methodology flood simulation improvement dynamical systems flood model calibration |
topic |
Ciencias Informáticas Parametric simulation tuning methodology flood simulation improvement dynamical systems flood model calibration |
dc.description.none.fl_txt_mv |
Scientists and engineers continuously build models to interpret axiomatic theories or explain the reality of the universe of interest to reduce the gap between formal theory and observation in practice. We focus our work on dealing with the uncertainty of the input data of the model to improve the quality of the simulation. To reduce this error, scientist and engineering implement techniques for model tuning and they look for ways to reduce their high computational cost. This article proposes a methodology for adjusting a simulator of a complex dynamic system that models the wave translation along rivers channels, with emphasis on the reduction of computation resources. We propose a simulator calibration by using a methodology based on successive adjustment steps of the model. We based our process in a parametric simulation. The input scenarios used to run the simulator at every step were obtained in an agile way, achieving a model improvement up to 50% in the reduction of the simulated data error. These results encouraged us to extend the adjustment process over a larger domain region. Trabajo publicado en <i>Lecture Notes in Computer Science</i> book series (LNCS, vol. 10862) Facultad de Informática |
description |
Scientists and engineers continuously build models to interpret axiomatic theories or explain the reality of the universe of interest to reduce the gap between formal theory and observation in practice. We focus our work on dealing with the uncertainty of the input data of the model to improve the quality of the simulation. To reduce this error, scientist and engineering implement techniques for model tuning and they look for ways to reduce their high computational cost. This article proposes a methodology for adjusting a simulator of a complex dynamic system that models the wave translation along rivers channels, with emphasis on the reduction of computation resources. We propose a simulator calibration by using a methodology based on successive adjustment steps of the model. We based our process in a parametric simulation. The input scenarios used to run the simulator at every step were obtained in an agile way, achieving a model improvement up to 50% in the reduction of the simulated data error. These results encouraged us to extend the adjustment process over a larger domain region. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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http://sedici.unlp.edu.ar/handle/10915/127483 |
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dc.language.none.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 639-646 |
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