摘要
鉴于公路工程建设风险评价属多维非线性问题,分析了混沌与神经网络相结合评价公路工程建设风险可行性,建立了混沌神经网络模型和评价指标体系,从而构建了完整的公路工程建设风险混沌神经网络评价系统(HCRCNNAS)。经实例研究表明,该系统评价结果稳定可靠,具有良好的应用前景。
As highway construction risk assessment is the problem of multi-dimension and nonlinear, this paper analyses feasibility of highway construction risk assessment by using chaos neural network, and establishes the chaos neural network model and evaluation indices system, thereby builds a complete highway construction risk chaos neural network assessment system （HCRCNNAS）. The research to actual examples shows that this system of evaluation result is stable and reliable,so it will have a good application prospect. Double bond of SBS reacted with the active functional group of asphalt by adding the multifunction modifier in the SBS modified asphalt . The result showed that some of the saturates and aromatics transformed into polycyclic resins. Three-dimensional space net-structures is formed between the SBS and original asphalt by chemical bonds . Therefore, the softening point of SBS modified asphalt was improved by 42.7% after modified by active Modifierl , the low temperature ductility was improved by 96.2% after modified by active Modifier2 ,the temperature stability are improved.
出处
《公路工程》
2008年第1期51-54,58,共5页
Highway Engineering
基金
交通部科技项目(2005309814030)
关键词
公路工程
混沌
神经网络
风险评价
Highway construction
Chaos
Neural network
Risk assessment
