Abordagem Adaptativa para um Algoritmo de Entropia Máxima na Modelagem de Nicho Ecológico (Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling)

Elisângela Silva da Cunha Rodrigues (elisangela.rodrigues@poli.usp.br), Fabricio Augusto Rodrigues (fabrício.rodrigues@poli.usp.br), Ricardo Luis de Azevedo da Rocha (rluis.rocha@poli.usp.br), Pedro Luiz Pizzigatti Corrêa (pedro.Correa@poli.usp.br)

University of São Paulo
This paper appears in: Revista IEEE América Latina

Publication Date: June 2011
Volume: 9,   Issue: 3 
ISSN: 1548-0992

This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works

Index Terms:
Adaptive systems, Biological system modeling,Maximum Entropy methods   

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