杨帆;吕磊;田振凯;何文义;

• 1:辽宁工程技术大学
• 2:黑龙江测绘地理信息局
• 3:阜新市国土资源局

摘要(Abstract)：

针对传统的变形预测模型不能对隧道高度非线性监测数据的沉降趋势和波动特征进行准确的预测问题,该文提出了反导自记忆模型。该模型运用了自记忆原理,克服了传统的变形预测模型对初值比较敏感、预测精度低等局限性,提高了对波动性数据的预测能力,之后通过工程实例验证了反导自记忆模型的可行性。最后与灰色自记忆模型进行对比,得出反导自记忆模型能够对非线性和波动性监测数据做出更加准确的预测,提高了预测的精度。

关键词(KeyWords)： 隧道沉降预测;自忆性原理;反导自记忆模型;沉降趋势

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(50604009);; 辽宁省“百千万人才工程”人选资助项目(2010921099);; 辽宁省教育厅重点实验室基础研究项目(LJZS001)

作者(Authors): 杨帆;吕磊;田振凯;何文义;

DOI: 10.16251/j.cnki.1009-2307.2017.12.017

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