| 基于AIGA-WLSSVM的埋地管道腐蚀速率预测方法 |
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| 引用本文： | 陈翀,赵超.基于AIGA-WLSSVM的埋地管道腐蚀速率预测方法[J].管道技术与设备,2017(3). |
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| 作者姓名： | 陈翀 赵超 |
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| 作者单位： | 福州大学石油化工学院,福建福州,350108 |
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| 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。
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| 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 |
Prediction Model for Buried Pipeline Corrosion Rate Based on AIGA-WLSSVM |
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| CHEN Chong,ZHAO Chao.Prediction Model for Buried Pipeline Corrosion Rate Based on AIGA-WLSSVM[J].Pipeline Technique and Equipment,2017(3). |
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| Authors: | CHEN Chong ZHAO Chao |
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| Abstract: | 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 parameters were used, thus improving the model learning ability and stability.The feasibility and effectiveness of AIGA-WLSSVM modeling method is verified by the example analysis in buried pipeline corrosion rate, thus providing reference for buried pipeline maintenance and replacement. |
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| Keywords: | buried pipeline corrosion rate adaptive immune genetic algorithm (AIGA) weighted least squares support vector machine (WLSSVM) prediction |
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