A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination

By J. Giraudel, Sovan Lek. 2001

363 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8ccde72b07a93bdcaaff71176cc19b3b9b93d039

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In Artificial Intelligence

Citations in the corpus

Bibliography of Self-Organizing Map SOM) Papers: 1998-2001 Addendum (2003, neutral): “PCA and ICA analysis of process control data obtained during si-wafer manufacturing.”
Modelling global insect pest species assemblages to determine risk of invasion (2006, background): “Successful results in aquatic community ecology using such models have been well documented (Chon et al . 1996; Cereghino, Giraudel & Compin 2001; Giraudel & Lek 2001; Park et al . 2003b).”
Quantitative metabolic profiles of tomato flesh and seeds during fruit development: complementary analysis with ANN and PCA (2007, methodology): “To apply the SOM algorithm, the Matlab software, 1.6.1 version was used with a program file written by the authors (Giraudel and Lek, 2001).”
Assessment of large-vertebrate species richness and relative abundance in Neotropical forest using line-transect censuses: what is the minimal effort required? (2008, positive): “This SOM method is expected to be much more powerful than classical ordination methods in ecological Welds (Brosse et al. 2001; Giraudel and Lek 2001; Brosse et al. 2007).”
Rapid evaluation of threats to biodiversity: human footprint score and large vertebrate species responses in French Guiana (2010, background): “SOM are known to provide an objective picture of the ecological structure in a data set, because they are not influenced by preconceived notions regarding the samples or the environment (Blayo and Demartines 1991; Chon et al. 1996; Giraudel and Lek 2001; Reyjol et al. 2005).”
Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application (2008, methodology): “In a related study, Giraudel and Lek (2001) utilized an SOM for clustering sample units (in species abundance database which consists of the species and the sample units) and visualization of species abundance by utilizing the component planes visualization technique.”