摘要
通过有限元法建立了刚性路面脱空的计算模型,提出采用基于集成神经网络技术对刚性路面脱空状况进行识别,通过刚性路面脱空输入特征向量的组合,用各子神经网络对刚性路面脱空进行初步缺陷识别,然后对识别结果进行决策融合,给出了系统的实现策略和子网络的组建原则。数值模拟结果表明,采用本识别方法合理地选取了各种输入特征向量,具有更好的识别效果．
A numerical calculating model of rigid pavement which can take the void of foundation is developed. The integrated neural networks void under rigid pavement plate identification technology is put forward based on the information fusion theory. Taking the sub- neural networks as primary separation identification from different sides, the conclusions are gained through decision -making fusion. The realizable policy of the identification system and established principle of the sub - neural networks are given. It can be educed from the numerical emulation examples that it takes full advantage of diversified characteristic information, and improves the diagnosis rate.
出处
《黑龙江大学自然科学学报》
CAS
北大核心
2005年第4期540-543,549,共5页
Journal of Natural Science of Heilongjiang University
