Dynamic Tuning of a Forest Fire Prediction Parallel Method
dc.creator | Caymes Scutari, Paola | |
dc.creator | Tardivo, María | |
dc.creator | Bianchini, Germán | |
dc.creator | Méndez Garabetti, Miguel | |
dc.date.accessioned | 2023-06-21T16:11:11Z | |
dc.date.available | 2023-06-21T16:11:11Z | |
dc.date.issued | 2020-01-01 | |
dc.description.abstract | Different parameters feed mathematical and/or empirical models. However, the uncertainty (or lack of precision) present in such parameters usually impacts in the quality of the output/recommendation of prediction models. Fortunately, there exist uncertainty reduction methods which enable the obtention of more accurate solutions. One of such methods is ESSIM-DE (Evolutionary Statistical System with Island Model and Differential Evolution), a general purpose method for prediction and uncertainty reduction. ESSIM-DE has been used for the forest fireline prediction, and it is based on statistical analysis, parallel computing, and differential evolution. In this work, we enrich ESSIM-DE with an automatic and dynamic tuning strategy, to adapt the generational parameter of the evolutionary process in order to avoid premature convergence and/or stagnation, and to improve the general performance of the predictive tool. We describe the metrics, the tuning points and actions, and we show the results for different controlled fires. | es_ES |
dc.description.affiliation | Universidad Tecnológica Nacional. Facultad Regional Mendoza; Argentina | es_ES |
dc.description.peerreviewed | Peer Reviewed | es_ES |
dc.format | es_ES | |
dc.identifier.citation | Springer Nature Switzerland AG 2020 | es_ES |
dc.identifier.doi | 10.1007/978-3-030-48325-8_2 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12272/8073 | |
dc.language.iso | eng | es_ES |
dc.rights | openAccess | es_ES |
dc.rights.holder | Universidad Tecnológica Nacional. Facultad Regional Mendoza | es_ES |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
dc.rights.uri | CC0 1.0 Universal | * |
dc.rights.use | Atribución | es_ES |
dc.source | Computer Science 1184, 19-34. (2020) | es_ES |
dc.subject | Dynamic tuning, Fire prediction, Differential Evolution, Parallel computing | es_ES |
dc.title | Dynamic Tuning of a Forest Fire Prediction Parallel Method | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.type.version | acceptedVersion | es_ES |