Case study: Comparing the use of nonlinear discriminating analysis and Artificial Neural Networks in the classification of three fish species: Acaras (Geophagus brasiliensis), tilapias (Tilapia rendalli) and mullets (Mugil liza)

Ecological Informatics

Volumn 5, Issue 6, 2010, Pages 474-478

  Hauser Davis, R A ^a   Oliveira, T F ^b   Silveira, A M ^b   Silva, T B ^c   Ziolli, R L ^a  

^a PONTIFICAL CATHOLIC UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^b FEDERAL UNIVERSITY OF PARÁ   (Brazil)

^c DEPARTAMENTO DE CIÊNCIAS BIOLÓGICAS   (Brazil)

Author keywords

Artificial Neural Networks; Discriminant Analysis; Geophagus brasiliensis; Mugil liza; Tilapia rendalli; Unbalanced data

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CICHLID; DISCRIMINANT ANALYSIS; ECOSYSTEM MANAGEMENT; ECOSYSTEM MODELING; ENDANGERED SPECIES; SPECIES CONSERVATION;

BRAZIL; RIO DE JANEIRO [BRAZIL];

ANIMALIA; GEOPHAGUS BRASILIENSIS; MUGIL LIZA; MUGILIDAE; TILAPIA; TILAPIA RENDALLI;

EID: 77957671450     PISSN: 15749541     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecoinf.2010.08.002     Document Type: Article

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