| 桥梁承载能力状态评估的模糊神经网络推理方法 |
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| 引用本文： | 钟珞,范剑锋,袁海庆,杨燕. 桥梁承载能力状态评估的模糊神经网络推理方法[J]. 华中科技大学学报(自然科学版), 2006, 34(3): 88-90 |
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| 作者姓名： | 钟珞 范剑锋 袁海庆 杨燕 |
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| 作者单位： | 武汉理工大学,计算机科学与技术学院,湖北,武汉,430070;武汉理工大学,道路桥梁与结构工程湖北省重点实验室,湖北,武汉,430070 |
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| 摘 要： | 在综合现有的状态评估理论方法的基础上,提出了基于层次分析的承载能力状态评估模型.结合模糊理论和神经网络技术,建立了一套基于监测信息输入的模糊神经网络推理系统框架,并利用模糊规则生成的规则库作为神经网络训练和学习的样本.利用实例验证了采用此智能评估技术进行承载能力状态评估的可行性和实用性.
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| 关 键 词： | 桥梁评估 承载能力状态 模糊规则 模糊推理 神经网络 隶属度函数 |
| 文章编号： | 1671-4512(2006)03-0088-03 |
| 收稿时间： | 2005-01-25 |
| 修稿时间： | 2005-01-25 |
Evaluation of bridge load-carrying capacity by fuzzy neural network method |
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| Zhong Luo,Fan Jianfeng,Yuan Haiqing,Yang Yan. Evaluation of bridge load-carrying capacity by fuzzy neural network method[J]. JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE, 2006, 34(3): 88-90 |
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| Authors: | Zhong Luo Fan Jianfeng Yuan Haiqing Yang Yan |
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| Affiliation: | Computer Science and Technology School, Wuhan University of Technology, Wuhan 430070, China |
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| Abstract: | Some theories and methods of condition evaluation were reviewed.A condition evaluation model of bridge bearing capacity was constructed.A set of fuzzy neural network Inference frame was built using fuzzy theory approach and neural network technology(taking monitoring information as input).As network samples,the rules created by the fuzzy rule were input to the neural network training and studying in the Inference frame.An example was executed to prove the feasibility and practicability in evaluating the bridge bearing capacity by the intelligent assessment technology. |
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| Keywords: | bridge evaluation bearing capacity evaluation fuzzy rule fuzzy reasoning neural network membership function |
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