Comparative analysis of performance and quality of prediction between ESS and ESS-IM
- Autores
- Méndez, Miguel Ángel; Bianchini, German; Tardivo, María Laura; Caymes Scutari, Paola Guadalupe
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Wildfires cause major damage and losses around the world. Such damages range from human and economical losses to environmental ones. Therefore, having models to predict their behavior can be a key element in the process of firefighting. In this paper, we present a comparative study between two methods we have developed. Both methods use Statistical Analysis, Parallel Evolutionary Algorithms and High Performance Computing, respectively named: Evolutionary-Statistical System (ESS) and Evolutionary-Statistical System with Island Model (ESS-IM). In this study, we have compared these two methods in terms of quality of prediction and performance in the parallel environment.
Fil: Méndez, Miguel Ángel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina
Fil: Bianchini, German. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina
Fil: Tardivo, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Computación; Argentina
Fil: Caymes Scutari, Paola Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina - Materia
-
EVOLUTIONARY ALGORITHMS
HIGH PERFORMANCE COMPUTING
SPEED-UP
WILDFIRES PREDICTION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/178557
Ver los metadatos del registro completo
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Comparative analysis of performance and quality of prediction between ESS and ESS-IMMéndez, Miguel ÁngelBianchini, GermanTardivo, María LauraCaymes Scutari, Paola GuadalupeEVOLUTIONARY ALGORITHMSHIGH PERFORMANCE COMPUTINGSPEED-UPWILDFIRES PREDICTIONhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Wildfires cause major damage and losses around the world. Such damages range from human and economical losses to environmental ones. Therefore, having models to predict their behavior can be a key element in the process of firefighting. In this paper, we present a comparative study between two methods we have developed. Both methods use Statistical Analysis, Parallel Evolutionary Algorithms and High Performance Computing, respectively named: Evolutionary-Statistical System (ESS) and Evolutionary-Statistical System with Island Model (ESS-IM). In this study, we have compared these two methods in terms of quality of prediction and performance in the parallel environment.Fil: Méndez, Miguel Ángel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; ArgentinaFil: Bianchini, German. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; ArgentinaFil: Tardivo, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Computación; ArgentinaFil: Caymes Scutari, Paola Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; ArgentinaElsevier2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/178557Méndez, Miguel Ángel; Bianchini, German; Tardivo, María Laura; Caymes Scutari, Paola Guadalupe; Comparative analysis of performance and quality of prediction between ESS and ESS-IM; Elsevier; Electronic Notes in Theoretical Computer Science; 314; 6-2015; 45-601571-0661CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1571066115000274info:eu-repo/semantics/altIdentifier/doi/10.1016/j.entcs.2015.05.004info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:23:13Zoai:ri.conicet.gov.ar:11336/178557instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:23:14.091CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM |
| title |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM |
| spellingShingle |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM Méndez, Miguel Ángel EVOLUTIONARY ALGORITHMS HIGH PERFORMANCE COMPUTING SPEED-UP WILDFIRES PREDICTION |
| title_short |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM |
| title_full |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM |
| title_fullStr |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM |
| title_full_unstemmed |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM |
| title_sort |
Comparative analysis of performance and quality of prediction between ESS and ESS-IM |
| dc.creator.none.fl_str_mv |
Méndez, Miguel Ángel Bianchini, German Tardivo, María Laura Caymes Scutari, Paola Guadalupe |
| author |
Méndez, Miguel Ángel |
| author_facet |
Méndez, Miguel Ángel Bianchini, German Tardivo, María Laura Caymes Scutari, Paola Guadalupe |
| author_role |
author |
| author2 |
Bianchini, German Tardivo, María Laura Caymes Scutari, Paola Guadalupe |
| author2_role |
author author author |
| dc.subject.none.fl_str_mv |
EVOLUTIONARY ALGORITHMS HIGH PERFORMANCE COMPUTING SPEED-UP WILDFIRES PREDICTION |
| topic |
EVOLUTIONARY ALGORITHMS HIGH PERFORMANCE COMPUTING SPEED-UP WILDFIRES PREDICTION |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
| dc.description.none.fl_txt_mv |
Wildfires cause major damage and losses around the world. Such damages range from human and economical losses to environmental ones. Therefore, having models to predict their behavior can be a key element in the process of firefighting. In this paper, we present a comparative study between two methods we have developed. Both methods use Statistical Analysis, Parallel Evolutionary Algorithms and High Performance Computing, respectively named: Evolutionary-Statistical System (ESS) and Evolutionary-Statistical System with Island Model (ESS-IM). In this study, we have compared these two methods in terms of quality of prediction and performance in the parallel environment. Fil: Méndez, Miguel Ángel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina Fil: Bianchini, German. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina Fil: Tardivo, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Computación; Argentina Fil: Caymes Scutari, Paola Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio de Investigación en Cómputo Paralelo/Distribuido; Argentina |
| description |
Wildfires cause major damage and losses around the world. Such damages range from human and economical losses to environmental ones. Therefore, having models to predict their behavior can be a key element in the process of firefighting. In this paper, we present a comparative study between two methods we have developed. Both methods use Statistical Analysis, Parallel Evolutionary Algorithms and High Performance Computing, respectively named: Evolutionary-Statistical System (ESS) and Evolutionary-Statistical System with Island Model (ESS-IM). In this study, we have compared these two methods in terms of quality of prediction and performance in the parallel environment. |
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2015 |
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2015-06 |
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http://hdl.handle.net/11336/178557 Méndez, Miguel Ángel; Bianchini, German; Tardivo, María Laura; Caymes Scutari, Paola Guadalupe; Comparative analysis of performance and quality of prediction between ESS and ESS-IM; Elsevier; Electronic Notes in Theoretical Computer Science; 314; 6-2015; 45-60 1571-0661 CONICET Digital CONICET |
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http://hdl.handle.net/11336/178557 |
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Méndez, Miguel Ángel; Bianchini, German; Tardivo, María Laura; Caymes Scutari, Paola Guadalupe; Comparative analysis of performance and quality of prediction between ESS and ESS-IM; Elsevier; Electronic Notes in Theoretical Computer Science; 314; 6-2015; 45-60 1571-0661 CONICET Digital CONICET |
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