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利用人工神经网络技术对碳钢在油田现场土壤中的腐蚀进行了研究。以试验点土壤的６种理化因素作为网络输入，以碳钢在这些土壤中的平均腐蚀速度和最大点蚀深度为输出。结果表明，调整好的网络对碳钢在土壤中的腐蚀预测误差较小，方法可行
Artificial neural network technology was used to study the corrosion of carbon steel in field oil field. Six kinds of physical and chemical factors of soil in test site were input as network, and the average corrosion rate and maximum pitting depth of carbon steel in these soil were output. The results show that the adjusted network has less error in predicting the corrosion of carbon steel in soil and the method is feasible