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1)  BKPLS
分块核偏最小二乘
1.
A method of block-wise kernel partial least-squares(BKPLS) was proposed to solve the problem of dimensional explosion of kernel matrix in batch-wise kernel partial least-squares(KPLS).
针对核偏最小二乘法(KPLS)随核函数矩阵维数膨胀而计算量增加的问题,提出分块核偏最小二乘法(BKPLS)。
2)  kernel partial least squares
核偏最小二乘
1.
To provide the necessary decision supports and analysis tools for quality control of strip hot-dip galvanizing,using the airknife parameters,a zinc coating weights forecasting model based on kernel partial least squares is proposed.
为了给带钢热镀锌生产的质量控制提供必要的决策支持和分析手段,针对气刀对锌层重量的控制工艺,提出了基于核偏最小二乘回归的锌层重量预测模型。
2.
A novel derivation based on optimization for the kernel partial least squares(K-PLS) algorithm is provided.
介绍了一个新的基于优化推导出的核偏最小二乘(kernel partial least squares,K-PLS)的算法原理和实现步骤,并且给出了利用K-PLS法构建P-糖蛋白(P-glycoprotein,P-gp)黄酮类抑制剂的定量构效关系(QSAR)模型。
3.
The new method couples kernel partial least squares(KPLS) feature extraction with support vector regression machine(SVR) to improve the quantitative analysis accuracy and speed of seven-component alkane gas mixtures composed of methane,ethane,propane,iso-butane,n-butane,iso-pentane,and n-pentane,whose feature absorption spectra are cross each other and overlapped seriously.
为进一步提高FTIR光谱法实现特征吸收光谱严重重叠的甲烷、乙烷、丙烷、异丁烷、正丁烷、异戊烷以及正戊烷七组分混合气体定量分析的精度和速度,提出一种核偏最小二乘(Kernel Partial Least Square,KPLS)特征提取耦合支持向量回归机(Support Vector Regression Machine,SVR)的红外光谱定量分析新方法。
3)  kernel partial least squares
核偏最小二乘法
4)  kernel partial least square (KPLS)
核的偏最小二乘
5)  block-wise recursive PLS
块式递推偏最小二乘
6)  kernel partial least squares
核心偏最小二乘法
1.
A wavelet soft thresholding kernel partial least squares (WSTKPLS) method was developed to perform simultaneous quantitative analysis of the mixture of o-dihydroxybenzene, m-dihydroxybenzene, p-dihydroxybenzene and phenol with overlapping spectra.
结合小波软阈值法和核心偏最小二乘法改进回归质量。
补充资料:最小辐亮度与最小辐照度(见核爆炸火球)


最小辐亮度与最小辐照度(见核爆炸火球)
minimum-brightness and minimum-irradiance

zuixiao fuliangdu yu zuixiaofu乙haodu最小辐亮度与最小辐照度(minimum-brightness and而nimum一irradianee)见核爆炸火球。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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