摘要
论文首先分析和总结了影响西安地裂缝发展变化的主要人为因素。随后,利用三维非稳定渗流分析方法研究了人类活动对地下水位的影响;根据西安市新增固定资产投资的变化,预测了地面荷载的变化;以时间、地下水位和地面荷载为基本变量,建立了预测f 7地裂缝活动趋势的BP神经网络模型;最后,借助MATLAB语言进行编程,利用训练稳定的网络模型,预测了f 7地裂缝的活动趋势以及年平均的垂直位移沉降量,为进一步研究西安地铁2号线安全运行和防护提供参考依据。
This paper analyzed and summarized in detail the main human factors that influence Xi＇an ground fis- sures. First human influence on groundwater level using the analytic method of 3-D unstable seepage was studied, and the ground load change was predicted based on the change of newly added investment on fixed assets of Xi＇ an ; Then taking time, underground water level and ground load as basic variables, a BP neural network model was built to predict the development tendency of 17 ground fissures, and finally, using the training stable model, the active development tendency and reference to safe operation the annual average vertical displacement of t7 ground fissures were predicted to present a of No. 2 subway line of Xi＇ an.
出处
《自然灾害学报》
CSCD
北大核心
2012年第3期170-176,共7页
Journal of Natural Disasters
基金
国家自然科学基金项目(50879069
50679073
90510017)
水利部公益性行业科研专项资助项目(2007SHZ1-20071004)
关键词
西安
地裂缝
累积垂直位移
预测研究
BP神经网络
Xi ! an
ground fissure
accumulated vertical displacement
predictive research
BP neural network
