统计回归 meaning in English
statistical regression
Examples
- With the distributions of bond stress and local slip , all specimens " bond - slip curves were simulated . and the calculating formula of characteristic slip and bond strength was conducted by mathematically disposal and statistically regression of bond - slip curves ; by revising the shape of bond - slip curves through " merge to one " , the model of bond - slip relation was confirmed and then a detailed definition on the model was conducted using position functions
结合粘结应力和局部滑移的分布规律，拟合出了各试件的粘结滑移曲线，然后对曲线进行一定的数学处理，经过统计回归后得到了特征滑移值和特征粘结强度的计算公式；对粘结滑移曲线形状经过“归一化”的数学处理进行修正，确定了基本的粘结滑移的本构关系式，并引入了一个位置函数对粘结滑移的本构关系进行了更为细致的描述。 - In all these 20 specimens , the embedded electronic steel - concrete slip transfer were respectively embedded on the steel shape webs and inside and outside of the flanges at certain intervals along the embedment length to measure the distributions of the interior slip , and the electronic strain gauges were also installed on the shallow grooves of each steel shape web and flanges at close intervals along the length to measure the distributions of the steel shape web and flanges strain , from which the distributions of bond stress were obtained . with these methods of measuring the distributions of slip and bond stresses , the establishment of the bond - slip constitutive relations were ensured
用力的平衡方程，得到推出试验中型钢混凝土粘结应力的大小及其分布规律;根据钢一混凝土电子滑移传感器的滑移量测结果，分析了沿型钢埋置长度的内部滑移分布规律，并对试验量测的特征滑移值进行了统计回归;根据粘结应力和内部滑移测量结果，得出沿型钢埋置长度方向上各截面的局部粘结应力一滑移关系曲线，建立了局部粘结滑移本构模型叹x )一s仁， ， … ， c ， … c 。 - An artificial neural network （ ann ） model was developed and used in different water bodies to predict timing for environmental changes as well as for the dynamics of resources . the results show that the ann model is superior to classical statistical models ( csm ) and can be used as predictive tool for highly non - linear phenomena
用人工神经网络方法对不同水域、不同环境因子之间非线性和不确定性的复杂关系进行学习训练并预测检验，结果表明:人工神经网络方法在模拟和预测方面均优于传统的统计回归模型，在资源与环境方面的应用是可行的，具有较强的模拟预测能力。 - Accuracy of ptfs is evaluated by the root of the mean squared difference ( rmsd ) . last , we compared measuring values with estimation values of regression method and bp model . the evaluating results indicate that ptfs developed by regression method or bp model satisfy to use to the education , research and production practice for keerqin sandy land
最后对统计回归模拟模型和dp神经网络模型进行了对比评价分析，对比分析结果表明，用两种模型建立土壤传递函数( ptfs )的预测效果都比较理想，均可应用于科尔沁沙地的教学、科研和生产实践中。 - ( 1 ) ptfs have been developed by using multivariate step wise regression analysis , nonlinear analysis and principle factor analysis . ( 2 ) back - propagation neural network ( bp ) was used in simulation and prediction of ptfs . we use theory of difference to evaluate ptfs developed whether regression method or bp model
不论是采用统计回归模拟模型，还是采用bp神经网络技术所建立的土壤传递函数( ptfs ) ，我们均用误差分析理论分析评价了两函数模型的有效性、适用性和精度，其精度通过均方差来衡量。