【摘要】：近十幾年以來人類對山體的工程活動逐年增加,由此造成的邊坡數(shù)量也逐年增多,但由人類對邊坡保護欠缺等原因造成的滑坡災(zāi)害也急劇增加。滑坡一旦發(fā)生便會造成不可估量的損失,因此為了能夠?qū)虏扇∠鄳?yīng)防范措施,減少滑坡災(zāi)害損失,我們針對易造成滑坡的邊坡體進行變形分析。邊坡變形分析能有效分析預(yù)測邊坡形變及其變化趨勢,因此它是一項非常有意義的工作。但由于重視程度和研究投入等各項差異,相比于國外發(fā)達國家的邊坡變形分析水平,我國在邊坡變形分析的準確性和高效性上還是有一定差距的。在以上研究背景及目的下,本文針對傳統(tǒng)邊坡變形分析理論模型進行研究,提出了一種全新的分析預(yù)測組合模型,即基于Kriging與改進灰色組合模型,其簡寫為K-改灰組合模型。該組合模型具有Kriging模型和灰色模型這兩種模型的優(yōu)點,能有效提高邊坡變形分析預(yù)測精度。本文主要的研究內(nèi)容可概括為以下幾點:(1)將地質(zhì)統(tǒng)計學(xué)中的Kriging理論運用于邊坡變形分析,說明了其思路來源,介紹了Kriging理論在邊坡變形分析中的優(yōu)勢與不足,并分析其理論可能性,列出了依據(jù)及假設(shè)。(2)對傳統(tǒng)灰色模型進行了相關(guān)改進,使得改進后的灰色模型具有“新陳代謝”功能,有效提高了灰色模型分析預(yù)測精度。(3)結(jié)合某一邊坡變形監(jiān)測實例,把Kriging和灰色理論應(yīng)用于邊坡形變位移量分析預(yù)測中。針對Kriging模型的建立,先統(tǒng)計分析得出Kriging模型變異函數(shù),而后在三維空間上運用等效應(yīng)橢圓原理套合Kriging球狀模型,最后最佳選取Kriging各方向插值模型。(4)探討如何解決改進灰色模型和Kriging模型權(quán)重分配問題,并把這兩個模型進行組合預(yù)測,然后利用各模型間的相關(guān)幾項指標進行精度評定對比,最后分析得出結(jié)論:相比于Kriging模型和灰色模型,K-改灰組合模型能很好結(jié)合這兩種模型各自的優(yōu)勢,其分析預(yù)測精度最高,Kriging模型和改進灰色模型這兩種模型分析預(yù)測精度次之,而灰色模型分析預(yù)測精度最低。
[Abstract]:In the past ten years, human engineering activities to the mountain have been increasing year by year, and the number of slope caused by this has also increased year by year, but the landslide disaster caused by the lack of human protection to the slope has also increased sharply. Once the landslide occurs, it will cause incalculable losses, so in order to take the corresponding preventive measures to the landslide and reduce the landslide disaster loss, we analyze the deformation of the slope which is prone to the landslide. Slope deformation analysis can effectively analyze and predict slope deformation and its changing trend, so it is a very meaningful work. However, due to the differences in the degree of attention and research input, compared with the level of slope deformation analysis in developed countries, there is still a certain gap in the accuracy and efficiency of slope deformation analysis in China. Under the above research background and purpose, this paper studies the traditional slope deformation analysis theory model, and puts forward a new combination model of analysis and prediction, that is, based on Kriging and improved grey combination model, which is abbreviated as the K-change grey combination model. The combined model has the advantages of Kriging model and grey model, and can effectively improve the accuracy of slope deformation analysis and prediction. The main research contents of this paper can be summarized as follows: (1) applying Kriging theory in geostatistics to slope deformation analysis, explaining its source of thinking, introducing the advantages and disadvantages of Kriging theory in slope deformation analysis. The theoretical possibility of the model is analyzed, and the basis and hypothesis are listed. (2) the traditional grey model is improved, which makes the improved grey model have the function of "metabolism". The prediction accuracy of grey model analysis is improved effectively. (3) combined with a slope deformation monitoring example, Kriging and grey theory are applied to the slope deformation displacement analysis and prediction. Aiming at the establishment of Kriging model, the variation function of Kriging model is obtained by statistical analysis, and then the Kriging spherical model is combined with the equal-effect elliptic principle in three dimensional space. Finally, the optimal selection of Kriging interpolation model in each direction. (4) discuss how to solve the weight distribution problem of improved grey model and Kriging model, and combine the two models to predict. Then, the accuracy of each model is evaluated and compared with each other. Finally, the conclusion is drawn that compared with Kriging model and grey model, the combination of K- grey model can combine the advantages of the two models. The precision of analysis and prediction is the highest, the Kriging model and the improved grey model are the second, and the grey model is the lowest.
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：P642.22

【參考文獻】

相關(guān)期刊論文 前5條

1 陳佳佳;陳偉清;;基于等維動態(tài)預(yù)測模型的建筑物變形分析[J];地礦測繪;2010年04期

2 陳樹德;;灰色模型的簡化計算[J];徐州工程學(xué)院學(xué)報(自然科學(xué)版);2009年04期

3 高旭光;高飛;;基于動態(tài)灰色模型的地面沉降預(yù)測[J];測繪;2010年03期

4 趙明華;劉小平;馮漢斌;彭文祥;;小灣電站高邊坡的穩(wěn)定性監(jiān)測及分析[J];巖石力學(xué)與工程學(xué)報;2006年S1期

5 蔣水華;彭銘;李典慶;張利民;周創(chuàng)兵;;考慮時效特性的錨固巖質(zhì)邊坡變形可靠度分析[J];巖石力學(xué)與工程學(xué)報;2013年06期

相關(guān)碩士學(xué)位論文 前5條

1 吳春廣;GM（1，1）模型的改進與應(yīng)用及其MATLAB實現(xiàn)[D];華東師范大學(xué);2010年

2 廖華容;路基邊坡沖刷機理及防護研究[D];湖南大學(xué);2012年

3 文靜;基于小波與灰色模型的滑坡時間預(yù)測預(yù)報[D];長安大學(xué);2012年

4 蔚清;邊坡監(jiān)測數(shù)據(jù)預(yù)處理方法比較及建模研究[D];合肥工業(yè)大學(xué);2013年

5 曹芳;虎頭崖礦床三維地質(zhì)建模與空間變異橢球體構(gòu)造[D];中南大學(xué);2013年

，

本文編號：2398232