APPLICATION OF GENETIC ALGORITHMS NEURAL NETWORKS IN PREDICTING CORROSION RATE OF CARBON STEEL
基于遗传算法的神经网络在预测油管钢腐蚀速率中的应用

For overcoming difficulties in application of the method of BP neural network, this paper proposed to optimize the neural network structure and connection weights by means of genetic algorithm whilst to reserve the best individual in evolution process, so that to build up a genetic algorithms Neural Networks model. Through an example we explain the application of this model in predicting the corrosion rate of carbon steel. Evidence shows that the predicted values accord with the values of laboratory tests very well. At last, the applicability of the generalization of the model was identified by use of the data from field tests. It shows that the predicted results closed to that of the field tests.