Forest fire prediction using fuzzy prototypical knowledge discovery

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...

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Detalles Bibliográficos
Autores principales: Olivas Varela, José Ángel, Romero, Francisco Pacual
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2000
Materias:
Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23461
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23461
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
spellingShingle Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
Olivas Varela, José Ángel
Romero, Francisco Pacual
Forest fire prediction using fuzzy prototypical knowledge discovery
topic_facet Ciencias Informáticas
Inteligencia Artificial
Data mining
Uncertainty, ``fuzzy,'' and probabilistic reasoning
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
format Objeto de conferencia
Objeto de conferencia
author Olivas Varela, José Ángel
Romero, Francisco Pacual
author_facet Olivas Varela, José Ángel
Romero, Francisco Pacual
author_sort Olivas Varela, José Ángel
title Forest fire prediction using fuzzy prototypical knowledge discovery
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
publishDate 2000
url http://sedici.unlp.edu.ar/handle/10915/23461
work_keys_str_mv AT olivasvarelajoseangel forestfirepredictionusingfuzzyprototypicalknowledgediscovery
AT romerofranciscopacual forestfirepredictionusingfuzzyprototypicalknowledgediscovery
bdutipo_str Repositorios
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