Evaluation of adaptive genetic algorithm to environmental modeling of peponapis and cucurbita

Renata Stange, Teresa Giannini, Fabiana SANTANA, Joao Neto, Antonio Saraiva

    Research output: Contribution to journalArticle

    Abstract

    The environmental modeling could be performed combining environmental data and species occurrence points in order to create distribution models, and this requires non trivial algorithms. The objective of this work is comparing GARP, one of the most used algorithms, with ADAPTGARP, that implements adaptive tools. The experiments considered some species of Peponapis and Cucurbita, respectively, pollinator insects and their plants. The maps with potential species distribution resulting from comparative experiments are very similar. The variations of AUC values, an accepted measure of accuracy on modeling, are also within the tolerance limits. The experiment shows that the algorithms are equivalent and the adaptive tools are adequate. Future works could be developed using adaptivity, such as including generic characteristics on the genetic algorithm and new types of treatment, looking for more accurate models
    Original languageEnglish
    Pages (from-to)171-177
    Number of pages7
    JournalIEEE America Latina. Revista
    Volume9
    Issue number2
    DOIs
    Publication statusPublished - 10 May 2011

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    Adaptive algorithms
    Genetic algorithms
    Experiments

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    Stange, Renata ; Giannini, Teresa ; SANTANA, Fabiana ; Neto, Joao ; Saraiva, Antonio. / Evaluation of adaptive genetic algorithm to environmental modeling of peponapis and cucurbita. In: IEEE America Latina. Revista. 2011 ; Vol. 9, No. 2. pp. 171-177.
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    abstract = "The environmental modeling could be performed combining environmental data and species occurrence points in order to create distribution models, and this requires non trivial algorithms. The objective of this work is comparing GARP, one of the most used algorithms, with ADAPTGARP, that implements adaptive tools. The experiments considered some species of Peponapis and Cucurbita, respectively, pollinator insects and their plants. The maps with potential species distribution resulting from comparative experiments are very similar. The variations of AUC values, an accepted measure of accuracy on modeling, are also within the tolerance limits. The experiment shows that the algorithms are equivalent and the adaptive tools are adequate. Future works could be developed using adaptivity, such as including generic characteristics on the genetic algorithm and new types of treatment, looking for more accurate models",
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    Evaluation of adaptive genetic algorithm to environmental modeling of peponapis and cucurbita. / Stange, Renata; Giannini, Teresa; SANTANA, Fabiana; Neto, Joao; Saraiva, Antonio.

    In: IEEE America Latina. Revista, Vol. 9, No. 2, 10.05.2011, p. 171-177.

    Research output: Contribution to journalArticle

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    AU - Stange, Renata

    AU - Giannini, Teresa

    AU - SANTANA, Fabiana

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