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基于MATLAB神经网络的埋地钢制管道土壤腐蚀等级评价

Assessment of Soil Corrosion Level for Buried Steel Pipeline Based on MATLAB Neural Network
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摘要 用MATLAB软件编写了神经网络训练和检验的子程序,构建了埋地钢制管道土壤腐蚀主要影响因素和土壤腐蚀等级之间的神经网络关系模型,并结合实地检测数据和相关标准规范对该模型进行了验证。结果表明,该模型能够对土壤腐蚀等级做出准确的评价,与传统评价方法相比效率较高。 Writing the subprogram of neural network training and validation with MATLAB software, build the neural network model between the main soil corrosion factors and soil corrosion level for buried steel pipeline, then validate the model with the inspection data and related standards and specifications. The results show that this model can make accurate assessment for soil corrosion level, compared with the traditional evaluation method, this model has better efficiency.
作者 程兴 刘礼良 唐国平 孙丽君 Cheng Xing;Liu Liliang;Tang Guoping;Sun Lijun(Guangdong Institute of Special Equipment Inspection and Research,Foshan 528251;Zhujiang Hospital of Southern Medical University,Guangzhou 510000)
出处 《中国化工装备》 CAS 2018年第4期41-48,共8页 China Chemical Industry Equipment
关键词 MATLAB 神经网络 埋地钢制管道 土壤腐蚀等级 MATLAB neural network buried steel pipeline soil corrosion level
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