| 应用人工神经网络技术评估混凝土中的钢筋锈蚀量 |
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| 引用本文： | 陈海斌 牛荻涛. 应用人工神经网络技术评估混凝土中的钢筋锈蚀量[J]. 工业建筑, 1999, 29(2): 51-55 |
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| 作者姓名： | 陈海斌 牛荻涛 |
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| 作者单位： | [1]上海建筑科学研究院 [2]西安建筑科技大学 |
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| 基金项目： | 国家基础研究和应用基础研究重大项目,国家自然科学基金 |
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| 摘 要： | 将人工神经网络技术应用于锈蚀开裂后混凝土中钢筋锈蚀量的评估，在分析锈蚀开裂后影响钢筋锈蚀量的主要因素基础上，建立了评估钢筋锈蚀量的人工神经网络模型，并从网络结构优化和学习参数的角度探讨了神经网络模型的适应性。最后通过实际工程检测结果验证了该方法的实际可行性。
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| 关 键 词： | 人工神经网络 钢筋锈蚀 |
ASSESSMENT ON CORROSIVE DEGREE OF REINFORCEMENT IN CONCRETE BY ARTIFICIAL NEURAL NETWORKS |
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| Chen HaibinNiu Ditao Pu Yuxiu. ASSESSMENT ON CORROSIVE DEGREE OF REINFORCEMENT IN CONCRETE BY ARTIFICIAL NEURAL NETWORKS[J]. Industrial Construction, 1999, 29(2): 51-55 |
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| Authors: | Chen HaibinNiu Ditao Pu Yuxiu |
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| Affiliation: | Chen HaibinNiu Ditao Pu Yuxiu (Shanghai Building Scientific Institute Shanghai 200032)(Xian Univ of Arch and Tech Xian 710055) |
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| Abstract: | Artificial neural networks is used for assessing corrosive degree of concrete embeded rebar after corrosion crack was produced After the main factor saffecting the corrosive degree of rebar is analysed,a neural networks model is founded The adaption of the model is discussed from the angles of networks structural optimization and learning parameters The feasibility is verified according to the data from practical engineering investigation |
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| Keywords: | artificial neural networks steel corrosion |
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