基于DFA和M-K检验的高层建筑沉降变形趋势判断研究
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摘要
为提高高层建筑沉降变形趋势判断的准确性,并探讨DFA和M-K检验在高层建筑沉降变形趋势判断中的适用性,从DFA和M-K检验的基本原理出发,构建了2个方法联合应用的高层建筑沉降变形趋势判断模型,并进一步探讨分析了AR(1)模型剔除沉降序列自相关性对分析结果的影响。通过2个实例的应用检验,得出DFA和M-K检验在高层建筑沉降变形趋势判断中的一致性较好,说明2种方法均能有效且准确的判断高层建筑的沉降变形趋势;同时,AR(1)模型能很好的剔除沉降序列的自相关性,减弱变形趋势判断的显著性,达到了提高分析结果可靠性的目的。通过研究,验证了DFA和M-K检验在高层建筑沉降变形趋势判断中的适用性,为2种方法的跨学科应用积累了经验,具有一定的参考价值。
Based on DFA analysis and M-K test, settlement deformation trend judgment model by two combined ways is built for the purpose of improving judgment accuracy of high rise buildings deformation trend and studying DFA and M-K test applicability for high rise buildings deformation trend. Based on DFA and M-K test, build settlement deformation trend judgment model by two combined ways, further to analyze the effect of autocorrelation on analyzed results after AR(1) model removes settlement sequence. By two real applying tests, it is concluded that the consistency of DFA and M-K test for high rise buildings deformation trend judgment is good, accounting for both two ways can affectively and accurately judge high rise buildings deformation trend; meanwhile, AR(1) model can well remove autocorrelation of settlement sequence, weaken significance of deformation trend judgment and achieve the purpose of improving the reliability of the analysis results. The DFA and M-K test applicability for high rise buildings deformation trend is verified by study, accumulating experience for application of two ways with a certain reference value.
Based on DFA analysis and M-K test, settlement deformation trend judgment model by two combined ways is built for the purpose of improving judgment accuracy of high rise buildings deformation trend and studying DFA and M-K test applicability for high rise buildings deformation trend. Based on DFA and M-K test, build settlement deformation trend judgment model by two combined ways, further to analyze the effect of autocorrelation on analyzed results after AR(1) model removes settlement sequence. By two real applying tests, it is concluded that the consistency of DFA and M-K test for high rise buildings deformation trend judgment is good, accounting for both two ways can affectively and accurately judge high rise buildings deformation trend; meanwhile, AR(1) model can well remove autocorrelation of settlement sequence, weaken significance of deformation trend judgment and achieve the purpose of improving the reliability of the analysis results. The DFA and M-K test applicability for high rise buildings deformation trend is verified by study, accumulating experience for application of two ways with a certain reference value.
引文
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[ 2 ] 陈继光.基于支持向量机模型的建筑物沉降预测[J].数学的实践与认识,2013,43(12):137-140.
[ 3 ] 喻伟,李百战,杨明宇,等.基于人工神经网络的建筑多目标预测模型[J].中南大学学报:自然科学版,2012,43(12):4949-4955.
[ 4 ] 段明旭,邱冬炜,李婉,等.改进灰色人工神经网络模型的超高层建筑变形预测[J].测绘科学,2017,42(4):141-146,183.
[ 5 ] 吴锋波,金淮,尚彦军,等.城市轨道交通隧道周边建(构)筑沉降预测方法研究[J].岩石力学与工程学报,2013,32(增刊2):3535-3544.
[ 6 ] 刘射洪,袁聚云,赵昕.软粘土地区超高层建筑沉降变形的时变性研究[J].地下空间与工程学报,2014,10(增刊2):1910-1916.
[ 7 ] 游强,游猛.流变模型在建筑地基沉降预测中的应用[J].地下空间与工程学报,2012,8(4):748-751.
[ 8 ] 李彦彬,黄强,徐建新,等.黄河近80年径流长程相关性诊断分析及趋势预测[J].干旱区资源与环境,2008,22(12):68-72.
[ 9 ] 张鑫,蔡焕杰,尹晓楠.基于DFA的无定河径流长期变化趋势及持续性研究[J].生态环境学报,2010,19(1):208-211.
[10] 李小丽,敖天其,黎小东.古蔺县近50年来降水序列趋势分析[J].水土保持研究,2016,23(6):140-144.
[11] 张洪波,王斌,辛琛,等.去趋势预置白方法对径流序列趋势检验的影响[J].水力发电学报,2016,35(12):56-69.
[12] 佟春生,黄强,刘涵,等.黄河径流序列标度不变性分析及趋势预测研究[J].自然资源学报,2007,22(4):86-86.
[13] 周安康,严宝文.渭河流域月径流序列分形特征研究[J].水力发电学报,2014,33(4):7-13.
[14] 李克昭,李志伟,赵磊杰.马尔科夫理论的优化灰色模型预测建模[J].测绘科学,2016,41(8):1-5.
[15] 朱军桃,李亚威,熊东旭,等.建筑物沉降监测中的改进灰色模型[J].测绘科学,2017,(11):1-10.