2015, 7(1): 95-98.
基于遗传神经网络的岩土参数优化反分析
南宁市财政局工程项目专项管理科，南宁 530022 |
Artificial Neural Network with Genetic Algorithm (GA-ANN) to Optimize and Feedback-analyze Mechanical Parameters of the Underground Works
Nanning Municipal Finance Bureau Special Project Management Division, Nanning 530022, China |
引用本文:
侯林波. 基于遗传神经网络的岩土参数优化反分析[J]. 土木建筑工程信息技术,
2015, 7(1): 95-98.
Citation:
Hou Linbo. Artificial Neural Network with Genetic Algorithm (GA-ANN) to Optimize and Feedback-analyze Mechanical Parameters of the Underground Works[J]. Journal of Information Technologyin Civil Engineering and Architecture,
2015, 7(1): 95-98.
摘要:由于地下工程岩土力学参数的复杂性，在实际工程设计和施工中，要想得到比较准确的岩土力学参数是比较困难的，而岩土参数对地下工程的设计和施工的成败具有很重要的意义。本文利用遗传神经网络优化算法结合数值模拟试验对地下工程岩土力学参数进行优化反分析，并取得了良好的效果。
Abstract: Due to the complexity of geotechnical parameters of the underground works, it is difficult to obtain accurate geotechnical parameters in actual design and construction, which is important to the success of design and construction of underground works. In this article, it achieves good results using Artificial Neural Network with Genetic Algorithm (GA-ANN) to optimize and feedback-analyze mechanical parameters of the underground works.
| [1] |
李守巨. 基于计算智能的岩土力学模型参数反演方法及工程应用. [博士论文], 大连: 大连理工大学, 2004. |
| [2] |
刘文卿.试验设计[M].北京:清华大学出版社, 2005, 2 |
| [3] |
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