Multivariate methods and artificial neural networks in the assessment of the response of infaunal assemblages to sediment metal contamination and organic enrichment

Science of the Total Environment

Volumn 450-451, Issue , 2013, Pages 289-300

  Subida, M D ^a   Berihuete, A ^b   Drake, P ^a   Blasco, J ^a  

^a INSTITUTO DE CIENCIAS MARINAS DE ANDALUCÍA   (Spain)

^b UNIVERSITY OF CÁDIZ   (Spain)

Author keywords

Artificial neural networks; Assessment; Infauna; Multivariate analysis; Sediment contamination; SOM

Indexed keywords

ASSESSMENT; INFAUNA; MULTI VARIATE ANALYSIS; SEDIMENT CONTAMINATION; SOM;

NEURAL NETWORKS; SEDIMENTS;

SEDIMENTOLOGY;

METAL;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BENTHOS; FAUNA; MULTIVARIATE ANALYSIS; SEDIMENT POLLUTION; SPATIOTEMPORAL ANALYSIS; TIDAL CHANNEL;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BENTHIC FAUNA; CONTROLLED STUDY; ECOLOGY; ENVIRONMENTAL ENRICHMENT; ESTUARY; INFAUNA; MULTIVARIATE ANALYSIS; NONHUMAN; PRIORITY JOURNAL; SEDIMENT; TAXON; UNIVARIATE ANALYSIS; WATER CONTAMINATION;

ANIMALS; AQUATIC ORGANISMS; ENVIRONMENTAL MONITORING; GEOLOGIC SEDIMENTS; HYDROCARBONS; METALS; MULTIVARIATE ANALYSIS; NEURAL NETWORKS (COMPUTER); SPAIN; SPATIO-TEMPORAL ANALYSIS; WATER POLLUTANTS, CHEMICAL;

EID: 84875244936     PISSN: 00489697     EISSN: 18791026     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2013.02.009     Document Type: Article

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