Calculation Models for Sediment Salinity in Coastal Areas Based on Artificial Neural Networks
The salinity of sediment is closely related to marine science,estuarine research,and environmental manage-ment.The existing formulas for calculating sediment salinity have some problems,such as lack of accuracy and limited ap-plicability.In view of this,this study carried out 271 sets of laboratory tests and 10 sets of field tests,and integrated the research data of other scholars.With sediment conductivity,sediment concentration,temperature and surface coefficient of fine particles as input variables,the back propagation artificial neural network(BP-ANN)model,particle swarm optimiza-tion back propagation artificial neural network(PSO-BP-ANN)model and genetic algorithm combined back propagation artificial neural network(GA-BP-ANN)model for calculating sediment salinity in coastal areas were established respec-tively.Compared with the existing sediment salinity calculation formulas,the new models have higher calculation accuracy and provide more alternative prediction methods for determining sediment salinity in coastal areas.
万方数据
维普
