运用人工神经网络研究苯胺及其衍生物在酸性介质中的缓蚀性能与分子结构参数的关系。研究对象包括苯胺在邻、间、对位的氟、氯、溴以及甲基取代物．建立了可用于预测苯胺类衍生物缓蚀效率的预测模型，并对苯胺邻、间、对位的碘、氰、羟基、甲氧基以及胺基取代物的缓蚀效率进行预测．探讨了结构参数对缓蚀剂的影响规律． Study on the Relationship between Corrosion Inhibition and Molecular Structure Parameters of Aniline and Its Derivatives in Acidic Media by Artificial Neural Network. The research objects include fluorine, chlorine, bromine and methyl substitutes of aniline in the ortho, meta and para positions. A prediction model that can be used to predict the corrosion inhibition efficiency of aniline derivatives was established. The inhibition efficiency of iodine, cyano, hydroxyl, methoxy and amino substituents of ortho-, meta- and para-anilines was predicted. The influence of structure parameters on corrosion inhibitor was discussed.