岩土力学
巖土力學
암토역학
Rock and Soil Mechanics
2015年
11期
3275-3282
,共8页
岩土参数%概率分布%大样本%正态信息扩散原理%窗宽
巖土參數%概率分佈%大樣本%正態信息擴散原理%窗寬
암토삼수%개솔분포%대양본%정태신식확산원리%창관
geotechnical parameters%probability distribution%large sample%principle of normal information spread%bandwidth
在重要的岩土工程中,确定大样本岩土参数的概率分布对岩土工程稳定性和可靠性分析有着极其重要的意义。为此,基于积分均方误差最小计算得到的最优窗宽,提出了推断大样本岩土参数概率密度函数的正态信息扩散法。该方法基于信息扩散原理,从试验样本和信息论的角度出发,充分利用样本提供的数据信息,而不是先假定成经典的概率分布曲线拟合检验,数学意义和物理意义更加充分和严密。以推断压缩指数 Cc的概率密度函数为例,分析了窗宽对信息扩散估计结果的影响规律,说明了该方法在大样本岩土参数概率密度函数推断方面的合理性。用该方法推断了大样本岩土抗剪强度参数的概率密度函数,通过K-S检验,验证了该方法的正确性和实用性。
在重要的巖土工程中,確定大樣本巖土參數的概率分佈對巖土工程穩定性和可靠性分析有著極其重要的意義。為此,基于積分均方誤差最小計算得到的最優窗寬,提齣瞭推斷大樣本巖土參數概率密度函數的正態信息擴散法。該方法基于信息擴散原理,從試驗樣本和信息論的角度齣髮,充分利用樣本提供的數據信息,而不是先假定成經典的概率分佈麯線擬閤檢驗,數學意義和物理意義更加充分和嚴密。以推斷壓縮指數 Cc的概率密度函數為例,分析瞭窗寬對信息擴散估計結果的影響規律,說明瞭該方法在大樣本巖土參數概率密度函數推斷方麵的閤理性。用該方法推斷瞭大樣本巖土抗剪彊度參數的概率密度函數,通過K-S檢驗,驗證瞭該方法的正確性和實用性。
재중요적암토공정중,학정대양본암토삼수적개솔분포대암토공정은정성화가고성분석유착겁기중요적의의。위차,기우적분균방오차최소계산득도적최우창관,제출료추단대양본암토삼수개솔밀도함수적정태신식확산법。해방법기우신식확산원리,종시험양본화신식론적각도출발,충분이용양본제공적수거신식,이불시선가정성경전적개솔분포곡선의합검험,수학의의화물리의의경가충분화엄밀。이추단압축지수 Cc적개솔밀도함수위례,분석료창관대신식확산고계결과적영향규률,설명료해방법재대양본암토삼수개솔밀도함수추단방면적합이성。용해방법추단료대양본암토항전강도삼수적개솔밀도함수,통과K-S검험,험증료해방법적정학성화실용성。
It is much more significant for assessment of probability distribution of large samples of geotechnical parameters to study the stability and reliability of geotechnical engineering in some important geotechnical engineerings. Thus normal information spread estimation method (NISEM) is proposed to generate probability density functions of geotechnical parameters with large samples based on the optimal bandwidth which is received by the minimum mean integrated square error. The method proposed in this paper based on the information spread principle, instead of assuming the fitting test of classical probability distribution curves, makes full use of the data sample provided from the view of the test sample and the information theory. It presents the mathematical and physical performances more fully and tight. The influence of bandwidth on the results of information diffusion estimation has been studied by the inference of probability density function of compression index (Cc). The results show the reasonability of NISEM, which is used to infer probability density function of geotechnical parameters with large samples. At last, probability density functions of rock and soil shear strength parameters have been inferred by using NISEM. By K-S test, the correctness and practicability of NISEM are verified.