Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

Park, Young‐Seuk; Céréghino, Régis; Compin, Arthur; Lek, Sovan

doi:10.1016/s0304-3800(02)00258-2

Cited by 365 publications

(260 citation statements)

References 40 publications

Supporting

Mentioning

251

Contrasting

Unclassified

Order By: Relevance

“…We utilized the SOM for patterning of macroinvertebrate communities (Ward, 1963;Park et al, 2003). The output layer consists of L r M computation nodes in the SOM.…”

Section: Sommentioning

confidence: 99%

“…The initialization and training processes followed suggestions by the SOM Toolbox by allowing optimization in a logarithm (Zurada, 1992;Chon et al, 1996;Vesanto et al, 2000) developed by the Laboratory of Information and Computer Science at the Helsinki University of Technology (http://www.cis.hut.fi/ projects/somtoolbox/) under Matlab environments (The Mathworks Inc., 2001). A detailed description regarding application of the SOM to ecological data is provided by Park et al (2003).…”

Section: Sommentioning

confidence: 99%

“…The self-organizing map (SOM) was utilized for extracting information from the metric data. The SOM has been an efficient tool for clustering and visualization of complex data without prior knowledge, and has been extensively used for patterning communities of benthic macroinvertebrates since the 1990s (Chon et al, 1996;Park et al, 2003;Song et al, 2007). The SOM was utilized for assisting with the screening procedure, covering discriminatory power, estimating the degree of association, and evaluating responsiveness to environmental impact.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Ecological informatics approach to screening of integrity metrics based on benthic macroinvertebrates in streams

Cho

Park

et al. 2011

Ann. Limnol. - Int. J. Lim.

Self Cite

View full text Add to dashboard Cite

-Benthic macroinvertebrates are considered as a representative taxon that indicates the ecological status of freshwater ecosystems. Numerous indices derived from community data have been proposed to estimate either biological water quality or ecosystem health. In this study, metrics based on benthic macroinvertebrates at the family level were screened using ecological informatics to provide a multi-metric measurement that would be suitable for presenting ecological integrity across different levels of environmental impact. Benthic macroinvertebrates were collected at a total of 720 sample sites from river basins and streams in Korea in 2009. Based on four categories of community status (i.e., diversity, richness, tolerance, and composition), 37 metrics were selected as initial candidates according to the literature. The candidate metrics were evaluated according to parameters including discriminatory power, redundancy, and responsiveness to stressors. Self-organizing map was utilized to assist the screening procedure by providing ordination, clustering, and visualization of metric and environmental data. Six metrics were finally selected as a multimetric and were compared with conventional indicators for presenting the ecological integrity of streams.

show abstract

“…We utilized the SOM for patterning of macroinvertebrate communities (Ward, 1963;Park et al, 2003). The output layer consists of L r M computation nodes in the SOM.…”

Section: Sommentioning

confidence: 99%

Section: Sommentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ecological informatics approach to screening of integrity metrics based on benthic macroinvertebrates in streams

Cho

Park

et al. 2011

Ann. Limnol. - Int. J. Lim.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The map obtained after the training process of the SOM contained all the macrofungi sites assigned to neurons so that similar sites were located in one neuron or in adjoining neurons, and significantly dissimilar sites were in distant neurons (Chon et al 1996;Park et al 2003;Bedoya et al 2009). To subdivide the output neurons into different clusters (groups) according to their similarity (Bedoya et al 2009), I used a hierarchical cluster analysis with the Ward linkage method and Euclidean distance measurements.…”

Section: Statistical Data Analysismentioning

confidence: 99%

Applications of self‐organizing map for patterning macrofungal diversity of xerothermic swards

Adamczyk

2011

Ecological Research

View full text Add to dashboard Cite

Macrofungal communities were investigated in four associations of xerothermic swards: Festucetum pallentis, Origano-Brachypodietum, Adonido-Brachypodietum pinnati and Diantho-Armerietum elongatae in a Jurassic area of the Częstochowa Upland (southern Poland). A total of 47 species were recorded. The selforganising map (SOM)-an unsupervised algorithm for artificial neural networks-was used to recognise patterns in the macrofungal communities of diverse xerothermic swards. Only two associations were mycologically similar: Origano-Brachypodietum and Adonido-Brachypodietum pinnati. Species with high and significant IndVal (the species indicator value) for each investigated phytocoenoses are presented. The presence of macrofungal species and the participation of indicator species were connected with habitat factors of plant associations, as documented by the IndVal application. In the least fertile phytocoenoses, macrofungal communities were poor with few indicator species. The more fertile phytocoenoses had richer and more varied communities of macrofungi with higher numbers of indicator species. The ordering methods applied in this study were very effective for analyzing the macrofungal communities existing in plant associations.

show abstract

“…In addition, ecological informatics has been developed to intensify data treatment and management during modeling. Artificial neural networks (ANNs) have also increasingly been used for complex data evaluation and modeling in various fields of ecology and environment sciences (Kwak et al, 2002;Park et al, 2003;Özesmi et al, 2006;Martín et al, 2008;Carafa et al, 2011), and have been reported to perform better than classical statistical methods for prediction and assessment (Lek and Guégan, 1999;Samecka-Cymerman et al, 2007). One of the best known ANNs containing unsupervised training algorithms is the Kohonen self-organizing map (SOM) (Kohonen, 1982), which allows classification of data without prior knowledge or assumptions.…”

Section: Introductionmentioning

confidence: 99%

Modeling macrozooplankton and water quality relationships after wetland construction in the Wenyuhe River Basin, China

Ren

Zeng

et al. 2013

Ecological Modelling

View full text Add to dashboard Cite

Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

Cited by 365 publications

References 40 publications

Ecological informatics approach to screening of integrity metrics based on benthic macroinvertebrates in streams

Ecological informatics approach to screening of integrity metrics based on benthic macroinvertebrates in streams

Applications of self‐organizing map for patterning macrofungal diversity of xerothermic swards

Modeling macrozooplankton and water quality relationships after wetland construction in the Wenyuhe River Basin, China

Contact Info

Product

Resources

About