Sea water quality assessment model using artificial neural networks

A new approach producing training set data, testing set data and critical values set data randomly distributed between the critical values was established in this paper. The principle of determining the number of hidden layers and their neurons on each layer was also discussed. And,the sea water quality assessment model using multi layer feedforward neural networks with error back propagation algorithm (NN based model) was set up. The NN based model possessed the capacity of higher generalization and not impacted by the initial values of connection weight. The assessed results of cases shown that the new presented NN based model was objective, reliable, practicable, and fault tolerant.