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.
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 hridge bearing capacity by the intelligent assessment technology.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第3期88-90,共3页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
湖北省科技攻关项目(2003AA101C76)
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
bridge evaluation
bearing capacity evaluation
fuzzy rule
fuzzy reasoning
neural network
membership function
