title: Hybrid modelling based on support vector regression with genetic algorithms in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain).
abstract: Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational waters. As a result, anticipate its presence is a matter of importance to prevent risks. The aim of this study is to use a hybrid approach based on support vector regression (SVR) in combination with genetic algorithms (GAs), known as a genetic algorithm support vector regression (GA-SVR) model, in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain). The GA-SVR approach is aimed at highly nonlinear biological problems with sharp peaks and the tests carried out proved its high performance. Some physical-chemical parameters have been considered along with the biological ones. The results obtained are two-fold. In the first place, the significance of each biological and physical-chemical variable on the cyanotoxins presence in the reservoir is determined with success. Finally, a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained.
authors: Department of Mathematics, Faculty of Sciences, University of Oviedo, 33007 Oviedo, Spain. lato@orion.ciencias.uniovi.es
authors: P J
authors: PJ
authors: García Nieto
authors: J R
authors: JR
authors: Alonso Fernández
authors: F J
authors: FJ
authors: de Cos Juez
authors: F
authors: F
authors: Sánchez Lasheras
authors: C
authors: C
authors: Díaz Muñiz
mesh_terms: D001427:Bacterial Toxins / Q000032:analysis*; D000458:Cyanobacteria; D000087522:Cyanobacteria Toxins; D005544:Forecasting; D008387:Marine Toxins / Q000032:analysis*; D052998:Microcystins / Q000032:analysis*; D012044:Regression Analysis; D013030:Spain; D060388:Support Vector Machine; D014871:Water Microbiology; D014881:Water Supply / Q000032:analysis*
chemical_list: D001427:Bacterial Toxins; D000087522:Cyanobacteria Toxins; D008387:Marine Toxins; D052998:Microcystins