| Prediction of mechanical property of E4303 electrode using artificial neural network |
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| 引用本文： | 徐越兰,黄俊,王克鸿. Prediction of mechanical property of E4303 electrode using artificial neural network[J]. 中国焊接, 2004, 13(2): 132-136 |
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| 作者姓名： | 徐越兰 黄俊 王克鸿 |
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| 作者单位： | DepartmentofMaterialsScienceandEngineering,NanjingUniversityofScienceandTechnology,Nanjing,210091 |
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| 摘 要： | Based on the method of artificial neural network, a new approach has been devised to predict the mechanical property of E4303 electrode. The outlined predication model for determining the mechanical propert) of electrode was built upon the production data. The research leverages a back propagation algorithm as the neural network‘ s learning rule. The result indicates that there are positive correlations between the predicted results and the practical production dota. Hence, using the neural network, predication of electrode property can be realized. For the first time, this research prorides a more scientific method for designing electrode.
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| 关 键 词： | 人工神经网络 电极设计 性质预测 焊接自动化 |
Prediction of mechanical property of E4303 electrode using artificial neural network |
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| Xu Yuelan,Huang Jun and Wang Kehong. Prediction of mechanical property of E4303 electrode using artificial neural network[J]. China Welding, 2004, 13(2): 132-136 |
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| Authors: | Xu Yuelan Huang Jun Wang Kehong |
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| Affiliation: | Department of Materials Science and Engineering,Nanjing University of Science and Technology,Nanjing,210094 |
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| Abstract: | Based on the method of artificial neural network, a new approach has been devised to predict the mechanical property of E4303 electrode. The outlined predication model for determining the mechanical property of electrode was built upon the production data. The research leverages a back propagation algorithm as the neural network's learning rule. The result indicates that there are positive correlations between the predicted results and the practical production data. Hence, using the neural network, predication of electrode property can be realized. For the first time, this research provides a more scientific method for designing electrode. |
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| Keywords: | artificial neural network electrode design property prediction |
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