Pages that link to "Item:Q1709394"

The following pages link to Predictive modelling of eutrophication in the Pozón de la Dolores lake (Northern Spain) by using an evolutionary support vector machines approach (Q1709394):

Displaying 7 items.

• A hybrid wavelet kernel SVM-based method using artificial bee colony algorithm for predicting the cyanotoxin content from experimental cyanobacteria concentrations in the Trasona reservoir (northern Spain) (Q313682) (← links)
• A hybrid PSO optimized SVM-based model for predicting a successful growth cycle of the \textit{Spirulina platensis} from raceway experiments data (Q491044) (← links)
• Ecological risk assessment of eutrophication in Songhua Lake, China (Q954729) (← links)
• Artificial neural networks and remote sensing in the analysis of the highly variable Pampean shallow lakes (Q1000267) (← links)
• A hybrid PSO optimized SVM-based method for predicting of the cyanotoxin content from experimental cyanobacteria concentrations in the trasona reservoir: a case study in northern Spain (Q1643054) (← links)
• Integrating support vector regression with particle swarm optimization for numerical modeling for algal blooms of freshwater (Q2282710) (← links)
• A hybrid DE optimized wavelet kernel SVR-based technique for algal atypical proliferation forecast in La Barca reservoir: a case study (Q2332723) (← links)