岩土力学
巖土力學
암토역학
ROCK AND SOIL MECHANICS
2013年
1期
173-181
,共9页
路基%沉降预测%多变量灰色模型%背景值%优化%新陈代谢方法
路基%沉降預測%多變量灰色模型%揹景值%優化%新陳代謝方法
로기%침강예측%다변량회색모형%배경치%우화%신진대사방법
subgrade%settlement prediction%multivariable grey model%background value%optimization%metabolism method
路基沉降是一个复杂的系统过程,常用的单点预测模型不能考虑各沉降监测点间的相关性,不足以反映路基整体的变形规律.多变量灰色模型 MGM(1, n)是单点 GM(1,1)模型在多元变量条件下的拓展,可以实现对路基中相互影响的多个监测点变形预测模型的建模和预测.针对传统多变量灰色模型背景值取值存在的误差,利用非齐次指数函数拟合模型中各变量的一次累加生成序列重构了背景值计算公式,提出了背景值优化的多变量灰色模型.对路基横断面上3个监测点进行了灰色关联分析,建立了相应的背景值优化的 MGM(1,3)模型,采用新陈代谢方法预测路基沉降值.实例计算表明,与传统 MGM (1, n)模型以及 GM(1,1)模型相比,背景值优化的多变量灰色模型具有更高的预测精度,显示了该方法进行路基沉降预测的有效性.
路基沉降是一箇複雜的繫統過程,常用的單點預測模型不能攷慮各沉降鑑測點間的相關性,不足以反映路基整體的變形規律.多變量灰色模型 MGM(1, n)是單點 GM(1,1)模型在多元變量條件下的拓展,可以實現對路基中相互影響的多箇鑑測點變形預測模型的建模和預測.針對傳統多變量灰色模型揹景值取值存在的誤差,利用非齊次指數函數擬閤模型中各變量的一次纍加生成序列重構瞭揹景值計算公式,提齣瞭揹景值優化的多變量灰色模型.對路基橫斷麵上3箇鑑測點進行瞭灰色關聯分析,建立瞭相應的揹景值優化的 MGM(1,3)模型,採用新陳代謝方法預測路基沉降值.實例計算錶明,與傳統 MGM (1, n)模型以及 GM(1,1)模型相比,揹景值優化的多變量灰色模型具有更高的預測精度,顯示瞭該方法進行路基沉降預測的有效性.
로기침강시일개복잡적계통과정,상용적단점예측모형불능고필각침강감측점간적상관성,불족이반영로기정체적변형규률.다변량회색모형 MGM(1, n)시단점 GM(1,1)모형재다원변량조건하적탁전,가이실현대로기중상호영향적다개감측점변형예측모형적건모화예측.침대전통다변량회색모형배경치취치존재적오차,이용비제차지수함수의합모형중각변량적일차루가생성서렬중구료배경치계산공식,제출료배경치우화적다변량회색모형.대로기횡단면상3개감측점진행료회색관련분석,건립료상응적배경치우화적 MGM(1,3)모형,채용신진대사방법예측로기침강치.실례계산표명,여전통 MGM (1, n)모형이급 GM(1,1)모형상비,배경치우화적다변량회색모형구유경고적예측정도,현시료해방법진행로기침강예측적유효성.
Subgrade settlement is a complex systematic process. Frequently used single point forecasting models can’t consider the correlation of settlement between the discrete monitoring points, so that it can’t represent the integrated deformation regularity of subgrade. A multivariable grey model named MGM(1,n), which is an extension of the single point model named GM(1,1), is introduced to solve the problem. According to the error of background value in the traditional multivariable grey model, this paper uses the functions with non-homogeneous exponential law to fit the accumulated sequences for every variable, reconstruct the calculating formula of background value, and gets a new multivariable grey model with optimized background value. Three monitoring points on the subgrade cross-section are analyzed by grey relational analysis theory. The corresponding MGM (1,3) model based on optimized background value is established; and the metabolism method is applied to predict subgrade settlement value. A case study shows that the forecast result of the proposed model is more precise and effective than these of the single-point grey model and the traditional multivariable grey model for predicting subgrade settlement.