One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles.In this paper,we propose a multiple linear regression method to retrieve sea...One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles.In this paper,we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0°65°.We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9,10.65,18.7,23.8 and 36.5 GHz.Then,the microwave radiative transfer forward model is used to simulate the measured brightness temperatures.The sensitivity of the brightness temperatures at 0°65°to the sea surface wind speed is calculated.Then,vertical polarization channels(VR),horizontal polarization channels(HR)and all channels(AR)are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0°65°,and the relationship between the retrieval error and incidence angle is obtained.The results are as follows:(1)The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization.(2)The retrieval error increases with Gaussian noise.The retrieval error of VR first increases and then decreases with increasing incidence angle,the retrieval error of HR gradually decreases with increasing incidence angle,and the retrieval error of AR first decreases and then increases with increasing incidence angle.(3)The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.展开更多
In this work, two chemometrics methods are applied for the modeling and prediction of electrophoretic mobilities of some organic and inorganic compounds. The successive projection algorithm, feature selection （SPA） ...In this work, two chemometrics methods are applied for the modeling and prediction of electrophoretic mobilities of some organic and inorganic compounds. The successive projection algorithm, feature selection （SPA） strategy, is used as the descriptor selection and model development method. Then, the support vector machine （SVM） and multiple linear regression （MLR） model are utilized to construct the non-linear and linear quantitative structure-property relationship models. The results obtained using the SVM model are compared with those obtained using MLR reveal that the SVM model is of much better predictive value than the MLR one. The root-mean-square errors for the training set and the test set for the SVM model were 0.1911 and 0.2569, respectively, while by the MLR model, they were 0.4908 and 0.6494, respectively. The results show that the SVM model drastically enhances the ability of prediction in QSPR studies and is superior to the MLR model.展开更多
基金National Natural Science Foundation of China(41475019,41631072)
文摘One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles.In this paper,we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0°65°.We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9,10.65,18.7,23.8 and 36.5 GHz.Then,the microwave radiative transfer forward model is used to simulate the measured brightness temperatures.The sensitivity of the brightness temperatures at 0°65°to the sea surface wind speed is calculated.Then,vertical polarization channels(VR),horizontal polarization channels(HR)and all channels(AR)are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0°65°,and the relationship between the retrieval error and incidence angle is obtained.The results are as follows:(1)The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization.(2)The retrieval error increases with Gaussian noise.The retrieval error of VR first increases and then decreases with increasing incidence angle,the retrieval error of HR gradually decreases with increasing incidence angle,and the retrieval error of AR first decreases and then increases with increasing incidence angle.(3)The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.
文摘In this work, two chemometrics methods are applied for the modeling and prediction of electrophoretic mobilities of some organic and inorganic compounds. The successive projection algorithm, feature selection （SPA） strategy, is used as the descriptor selection and model development method. Then, the support vector machine （SVM） and multiple linear regression （MLR） model are utilized to construct the non-linear and linear quantitative structure-property relationship models. The results obtained using the SVM model are compared with those obtained using MLR reveal that the SVM model is of much better predictive value than the MLR one. The root-mean-square errors for the training set and the test set for the SVM model were 0.1911 and 0.2569, respectively, while by the MLR model, they were 0.4908 and 0.6494, respectively. The results show that the SVM model drastically enhances the ability of prediction in QSPR studies and is superior to the MLR model.
