Support Vector Machines and Multilayer Perceptron Networks Used to Evaluate the Cyanotoxins Presence from Experimental Cyanobacteria Concentrations in the Trasona Reservoir (Northern Spain)

Water Resources Management

Volumn 27, Issue 9, 2013, Pages 3457-3476

  Vilan Vilan J A ^a   Alonso Fernandez J R ^b   Garcia Nieto P J ^c   Sanchez Lasheras F ^c   de Cos Juez, F J ^c   Diaz Muniz C ^b  

^a UNIVERSITY OF VIGO   (Spain)

^b Ministerio de Agricultura Alimentación y Medio Ambiente   (Spain)

^c UNIVERSITY OF OVIEDO   (Spain)

Author keywords

Cyanobacteria; Cyanotoxins; Multilayer perceptron networks (MLP); Regression analysis; Statistical learning techniques; Support vector machines (SVM)

Indexed keywords

CYANOBACTERIA; CYANOBACTERIA BLOOMS; CYANOBACTERIAL TOXINS; CYANOTOXINS; INNOVATIVE RESEARCH; MULTI-LAYER PERCEPTRON NETWORKS; MULTILAYER PERCEPTRON NETWORK (MLP); STATISTICAL LEARNING TECHNIQUES;

ALGAE; REGRESSION ANALYSIS; RESERVOIRS (WATER);

SUPPORT VECTOR MACHINES;

ALGAL BLOOM; CYANOBACTERIUM; EXPERIMENTAL STUDY; MATHEMATICAL ANALYSIS; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; PHYSICOCHEMICAL PROPERTY; REGRESSION ANALYSIS; RESERVOIR; RISK ASSESSMENT; TOXICITY TEST;

ASTURIAS; SPAIN; TRASONA RESERVOIR;

CHLOROPHYTA; CYANOBACTERIA;

EID: 84878760622     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-013-0358-4     Document Type: Article

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