Forest fire prediction using fuzzy prototypical knowledge discovery

Autores
Olivas Varela, José Ángel; Romero, Francisco Pacual
Año de publicación
2000
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
An application of Zadeh’s prototype theory in the Knowledge Acquisition process, is presented here, and as a practical example, to define a method for predicting the evolution of the forest fire occurrence-danger rate in INCEND-IA: A KBS for prediction and decision support in fighting against forest fires. This method then allows us to interpret any real cyclical situation using a previously discovered paradigm and define the current period. The FPKD (Fuzzy Prototypical Knowledge Discovery) is presented as a mechanism with the aim of generating Prototypes of Data (A new set of data sufficiently representative to be able to summarize or assimilate the behavior of any of the remaining data); but the concept of prototype is a fuzzy concept and Zadeh’s Theory provides an appropriate framework for its application. Data Mining techniques have been used (decision trees, time series, clustering...). Thus, it is possible to calculate the grade of compatibility of a real situation with the prototypes and define the current period using these affinity values, with the objective of predicting the evolution of the following days
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23461

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network_name_str SEDICI (UNLP)
spelling Forest fire prediction using fuzzy prototypical knowledge discoveryOlivas Varela, José ÁngelRomero, Francisco PacualCiencias InformáticasInteligencia ArtificialData miningUncertainty, ``fuzzy,'' and probabilistic reasoningAn application of Zadeh’s prototype theory in the Knowledge Acquisition process, is presented here, and as a practical example, to define a method for predicting the evolution of the forest fire occurrence-danger rate in INCEND-IA: A KBS for prediction and decision support in fighting against forest fires. This method then allows us to interpret any real cyclical situation using a previously discovered paradigm and define the current period. The FPKD (Fuzzy Prototypical Knowledge Discovery) is presented as a mechanism with the aim of generating Prototypes of Data (A new set of data sufficiently representative to be able to summarize or assimilate the behavior of any of the remaining data); but the concept of prototype is a fuzzy concept and Zadeh’s Theory provides an appropriate framework for its application. Data Mining techniques have been used (decision trees, time series, clustering...). Thus, it is possible to calculate the grade of compatibility of a real situation with the prototypes and define the current period using these affinity values, with the objective of predicting the evolution of the following daysI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2000-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23461enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:26Zoai:sedici.unlp.edu.ar:10915/23461Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:26.887SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Forest fire prediction using fuzzy prototypical knowledge discovery
title Forest fire prediction using fuzzy prototypical knowledge discovery
spellingShingle Forest fire prediction using fuzzy prototypical knowledge discovery
Olivas Varela, José Ángel
Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
title_short Forest fire prediction using fuzzy prototypical knowledge discovery
title_full Forest fire prediction using fuzzy prototypical knowledge discovery
title_fullStr Forest fire prediction using fuzzy prototypical knowledge discovery
title_full_unstemmed Forest fire prediction using fuzzy prototypical knowledge discovery
title_sort Forest fire prediction using fuzzy prototypical knowledge discovery
dc.creator.none.fl_str_mv Olivas Varela, José Ángel
Romero, Francisco Pacual
author Olivas Varela, José Ángel
author_facet Olivas Varela, José Ángel
Romero, Francisco Pacual
author_role author
author2 Romero, Francisco Pacual
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
topic Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
dc.description.none.fl_txt_mv An application of Zadeh’s prototype theory in the Knowledge Acquisition process, is presented here, and as a practical example, to define a method for predicting the evolution of the forest fire occurrence-danger rate in INCEND-IA: A KBS for prediction and decision support in fighting against forest fires. This method then allows us to interpret any real cyclical situation using a previously discovered paradigm and define the current period. The FPKD (Fuzzy Prototypical Knowledge Discovery) is presented as a mechanism with the aim of generating Prototypes of Data (A new set of data sufficiently representative to be able to summarize or assimilate the behavior of any of the remaining data); but the concept of prototype is a fuzzy concept and Zadeh’s Theory provides an appropriate framework for its application. Data Mining techniques have been used (decision trees, time series, clustering...). Thus, it is possible to calculate the grade of compatibility of a real situation with the prototypes and define the current period using these affinity values, with the objective of predicting the evolution of the following days
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description An application of Zadeh’s prototype theory in the Knowledge Acquisition process, is presented here, and as a practical example, to define a method for predicting the evolution of the forest fire occurrence-danger rate in INCEND-IA: A KBS for prediction and decision support in fighting against forest fires. This method then allows us to interpret any real cyclical situation using a previously discovered paradigm and define the current period. The FPKD (Fuzzy Prototypical Knowledge Discovery) is presented as a mechanism with the aim of generating Prototypes of Data (A new set of data sufficiently representative to be able to summarize or assimilate the behavior of any of the remaining data); but the concept of prototype is a fuzzy concept and Zadeh’s Theory provides an appropriate framework for its application. Data Mining techniques have been used (decision trees, time series, clustering...). Thus, it is possible to calculate the grade of compatibility of a real situation with the prototypes and define the current period using these affinity values, with the objective of predicting the evolution of the following days
publishDate 2000
dc.date.none.fl_str_mv 2000-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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