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It was based on t he Gauss distribution and conformal transformation method presented by Amari and Wu.

分析了确定数据分布特征的重要性,给出了判断数据呈高斯分布的方法,探讨了SVM核函数及其参数选择与数据分布的相关性。

Both the fuzziness and the randomness of the basic variable and the state variable are considered in the present method.

结合工程实际,提出了非闭合隶属函数的截断可能性分布模型,并对模糊强度和模糊应力进行截断处理,给出了结构模糊随机失效概率随截断参数的分布,并给出了结构模糊随机失效概率分布的数值计算方法。

The response variable is fitted with Poisson and negative binomial distributions,and the coefficient is estimated with IGLS.

分布函数采用Poisson分布和负二项分布,参数估计为迭代广义最小二乘法。

On the basis of the pressure correcting method about the measurement of bubble size distribution a photoelectrical capillary probe technique with a micro-computer on line was successfully used to study in detail the effects of various operating parameters such as gas rate, feed rate, feed concentration, NaCl concentration in solution, gas bubbler and gas bubbling state on bubble and foam bubble size distributions in foam fractionation column.

在已建立的光电毛细探头技术测定气泡尺寸分布的压力校正方法基础上,应用光电毛细探头微机在线测量方法,研究了各种操作参数,如气体流速、进料量、进料浓度、溶液中NaCl浓度、气体分布器以及布气状态等,对泡沫分离塔内气泡和泡沫气泡尺寸与分布的影响。

The technique of parameters normalization based on piecewise estimating the cumulative distribution function is performed in this paper. In this way the non-Gaussianity in the means of the cumulative distribution of Mel-cepstral parameters is decreased. Thus GMMs with fewer mixtures could model them precisely.

本文提出了一种基于分段估计概率分布函数的规整方法,在概率分布的意义上降低特征参数偏离高斯分布的程度,从而可以用较低混合度的高斯混合模型对其建模。

With selecting earlap as the measuring spot,a multi-layer simulation model of the earlap is established.The transmittance of the earlap model and its distribution regularities under vary beam properties(beam radius,the input energy and its distribution) and model parameters are researched by Monte-Carlo method.

选择耳垂作为测量部位,建立了多层耳垂组织仿真模型,利用Monte-Carlo方法研究了不同光源特性(光束半径,入射能量大小及分布等)及模型参数下耳垂组织模型的光透射能量及分布规律,由透射光能量分布、光电二极管光敏面积和探测灵敏度推出特定测量信噪比要求的入射光能量。

The distribution function of the system response and state function is approximately determined by the standard normal distribution functions using Edgeworth series, and its reliability is obtained.

在结构系统响应和状态函数的前四阶矩的一般数学表达式的基础上,使用 Edgeworth级数把未知响应和状态函数的概率分布展开成标准的正态分布表达式,并放松了对随机参数的分布概型和激励类型的限制,从而确定了系统的可靠度

And objective parameters (texturized degree, color, hardness, springiness, chewing, water absorption, yield, etc.) were investigated in the high moisture soy protein extrusion process, and the statistical models of system and objective parameters were built, using the step-by-step regression analysis; A comprehensive evaluation of the products, and the process optimization of high moisture extrusion were obtained,using factor analysis; Secondly, residence time distribution and soy isoflavones losses kinetics were studied in the high moisture extrusion; Finally, chemical bonding process, the micro-structure and protein secondary structure changes were investigated in the texturization of soy protein, then the mechanism assumptions of texturization soy protein by moisture extrusion were proposed.

本文对大豆蛋白高水分挤压组织化技术和机理进行了研究,研究内容包括:首先采用系统分析法,研究了大豆蛋白高水分挤压过程中,挤压机操作参数(螺杆转速、物料水分、喂料速度和机筒温度)对系统参数(系统压力、扭矩、单位机械能等)、目标参数(组织化度、色泽、硬度、弹性、咀嚼性、吸水率、产量等)的影响规律,建立了各因变参数的统计模型;采用因子分析法对产品进行了综合评价,并对高水分挤压组织化工艺进行了优化;其次,研究了大豆蛋白高水分挤压中的停留时间分布以及大豆异黄酮的损失动力学;最后,研究了大豆蛋白组织化过程中化学键、微观结构和蛋白质二级结构的变化规律,提出了大豆蛋白高水分挤压组织化的机理假设。

The last section of chapter 3 discusses the local sensitivityof the Bayes VaR when the contaminated probability ε close to zero. Consider adifferent contaminated class 〓,where Q consists ofsuch functions q that π can be regulized to be a proper probability distribution.

当〓是由定义在参数空间上的所有概率分布组成的分布类时,在没有观测数据和存在观测数据两种情况下,我们分别得到了基准先验分布〓下BayesVaR在ε污染类上对应概率水平的变化范围,该范围越小,表示基准先验分布下BayesVaR的稳健性越好,该范围越大意味着稳健性越差。

The probability distribution function and the corresponding statistical parameters of sharing ratio of internal pressure in bedrock for embedded penstocks in terms of design reference per.

根据已搜集到的国内外部分水电站地下埋管围岩内压分担率的实测数据,利用统计数学中的K-S法和A-D法等检验方法进行了统计分析和分布假设检验,求得了水电站地下埋管围岩内压分担率在设计基准期内的概率分布函数及其统计参数,证明其最优概率分布函数可用对数正态分布来拟合。

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