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Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling

Authors
  • RODRIGUES, E. S. C.
  • RODRIGUES, F. A.
  • ROCHA, R. L. A.
  • CORREA, P. L. P.
Publication Date
Jan 01, 2011
Source
Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Keywords
Language
English
License
Unknown
External links

Abstract

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.

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