• 还根据所得寿命分布作出了DVP-S-N曲线据此推断出极限应力分布规律可以用威布尔分布态分布描述。

    Furthermore, the P-S-N curves of D type V belt are plotted and the distribution of limit stress are deduced.

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  • 可避免不一致性可能导致多重模态分布分布,可能会应用程序性能造成可度量影响

    Avoidable inconsistencies may lead to multimodal or non-normal distributions and may have a measurable impact on application performance.

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  • 由于威布尔分布对数正态分布常用分析寿命分布问题优先考虑两种模型

    Weibull distribution or lognormal distribution is often used to analyze lifetime problem, so the two models are preferentially considered in tis paper.

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  • 一化以后数据服从同一正态分布可以减少消除不等精度干扰突出图象中的有用信息

    The normalized data will exhibit the same normal distribution, reduce or eliminate the interference of unequal precision, and highlight the useful information in images.

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  • 抗差估计等价函数一般正态分布统计构造临界值称准则)一般实际经验确定

    The equivalent weight function in robust estimation is usually constructed by the statistics of normal distribution. The critical values are often fixed by experience.

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  • 线性回归模型误差项服从分布存在多个可以秩次的某些函数作为权重引入估计模型来减少离群点的不良影响。

    When multiple outliers occur in linear regression model or the distribution of residuals is not normal, we can use residuals rank as weight function to get some resist estimator.

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  • 形变量大于等于70 %时,结晶晶粒尺寸分布符合对数正态分布

    If the cold deformation rate is higher than 70 %, the recrystallized grain size distribution agrees with lognormal distribution.

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  • 结果检验频率分布曲线分析显示,所获数据符合基本符合正态分布

    A normal distribution of our data was shown using the normality test and distribution curve.

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  • 传统回归分析适用来自分布完全数据,对于截尾数据布尔分布数据则无能为力,目前工程上只能采用成组试验方法,结果导致试验很大

    The traditional regression analysis is only suitable to complete data from normal distribution. In engineering, censored data is analyzed by group test method that requires a large number of samples.

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  • 传统回归分析适用来自分布完全数据,对于截尾数据布尔分布数据则无能为力,目前工程上只能采用成组试验方法,结果导致试验很大

    The traditional regression analysis is only suitable to complete data from normal distribution. In engineering, censored data is analyzed by group test method that requires a large number of samples.

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