摘要
为了降低埋地管道腐蚀影响因素之间的复杂相关性,提高腐蚀预测精度,文中提出一种基于自适应免疫遗传算法-加权最小二乘支持向量机(AIGA-WLSSVM)的埋地管道腐蚀速率预测建模方法,并采用AIGA优化模型参数,进一步提高模型的学习能力和稳定性。最后通过实例分析验证了AIGA-WLSSVM建模方法在埋地管道腐蚀速率预测中的可行性和有效性,为埋地管道的检修与更换提供参考。
In order to reduce the complex correlation of the corrosion influence factors of buried pipeline and improve the pipeline corrosion prediction precision, the adaptive immune genetic algorithm-weighted least squares support vector machine （AIGA-WLSSVM） was used to propose the corrosion rate prediction model of buried pipeline. AIGA optimization model parame- ters were used, thus improving the model learning ability and stability. The feasibility and effectiveness of AIGA-WLSSVM mod- eling method is verified by the example analysis in buried pipeline corrosion rate, thus providing reference for buried pipeline ma- intenance and replacement.
出处
《管道技术与设备》
CAS
2017年第3期34-38,共5页
Pipeline Technique and Equipment
关键词
埋地管道
腐蚀速率
自适应免疫遗传算法
加权最小二乘支持向量机
预测
buried pipeline
corrosion rate
adaptive immune genetic algorithm （AIGA）
weighted least squares support vector ma- chine （WLSSVM）
prediction
