To overcome the excessive computational cost and/or bad accuracy of traditional approaches,the probabilistic density evolution method(PDEM) is introduced.The dynamic reliability of a double-layer cylindrical latticed ...To overcome the excessive computational cost and/or bad accuracy of traditional approaches,the probabilistic density evolution method(PDEM) is introduced.The dynamic reliability of a double-layer cylindrical latticed shell is evaluated by applying PDEM and Monte Carlo Method(MCM) respectively,and four apparent wave velocities(100 m/s,500 m/s,800 m/s and 1 200 m/s) and five thresholds(0.1 m,0.2 m,0.3 m,0.4 m and 0.5 m) are taken into consideration.Only the difference between threshold and maximal deformation...展开更多
In this paper, we propose a new method that combines collage error in fractal domain and Hu moment invariants for image retrieval with a statistical method - variable bandwidth Kernel Density Estimation (KDE). The pro...In this paper, we propose a new method that combines collage error in fractal domain and Hu moment invariants for image retrieval with a statistical method - variable bandwidth Kernel Density Estimation (KDE). The proposed method is called CHK (KDE of Collage error and Hu moment) and it is tested on the Vistex texture database with 640 natural images. Experimental results show that the Average Retrieval Rate (ARR) can reach into 78.18%, which demonstrates that the proposed method performs better than the one with parameters respectively as well as the commonly used histogram method both on retrieval rate and retrieval time.展开更多
Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflect...Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters,comprising leaf area index (LAI;m-2 green leaf area m-2 soil) and green leaf chlorophyll density (GLCD;mg chlorophyll m 2 soil),using stepwise multiple regression (SMR) models and support vector machines (SVMs).Four transformations of the rice canopy data were made,comprising reflectances (R),first-order derivative reflectances (D1),second-order derivative reflectances (D2),and logarithm transformation of reflectances (LOG).The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI,with a root mean square error (RMSE) of 1.0496 LAI units.The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD,with an RMSE of 523.0741 mg m-2.The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters,but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.展开更多
We propose a new type of dark energy （DE） model, in which the equation of state of DE wae is a simple function of the fractional energy density Ωde instead of the redshift z. We assume three DE models of this type,...We propose a new type of dark energy （DE） model, in which the equation of state of DE wae is a simple function of the fractional energy density Ωde instead of the redshift z. We assume three DE models of this type, and fit them with present observations to get constraints of DE, which are also compared with the CPL model. It is shown that a suitable wda,（Ωde） model can give smaller X2 or smaller errors of wde than that of the CPL model. This new type of DE model can help to study the essential properties and nature of DE.展开更多
基金Supported by National Natural Science Foundation of China (No.50478094)
文摘To overcome the excessive computational cost and/or bad accuracy of traditional approaches,the probabilistic density evolution method(PDEM) is introduced.The dynamic reliability of a double-layer cylindrical latticed shell is evaluated by applying PDEM and Monte Carlo Method(MCM) respectively,and four apparent wave velocities(100 m/s,500 m/s,800 m/s and 1 200 m/s) and five thresholds(0.1 m,0.2 m,0.3 m,0.4 m and 0.5 m) are taken into consideration.Only the difference between threshold and maximal deformation...
基金Supported by the Fundamental Research Funds for the Central Universities (No. NS2012093)
文摘In this paper, we propose a new method that combines collage error in fractal domain and Hu moment invariants for image retrieval with a statistical method - variable bandwidth Kernel Density Estimation (KDE). The proposed method is called CHK (KDE of Collage error and Hu moment) and it is tested on the Vistex texture database with 640 natural images. Experimental results show that the Average Retrieval Rate (ARR) can reach into 78.18%, which demonstrates that the proposed method performs better than the one with parameters respectively as well as the commonly used histogram method both on retrieval rate and retrieval time.
基金supported by the National Natural Science Foundation of China(Grant Nos. 40571115 and 40271078)the National Hi-Tech Research and Development Program of China(Grant No. 2006AA10Z203)
文摘Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters,comprising leaf area index (LAI;m-2 green leaf area m-2 soil) and green leaf chlorophyll density (GLCD;mg chlorophyll m 2 soil),using stepwise multiple regression (SMR) models and support vector machines (SVMs).Four transformations of the rice canopy data were made,comprising reflectances (R),first-order derivative reflectances (D1),second-order derivative reflectances (D2),and logarithm transformation of reflectances (LOG).The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI,with a root mean square error (RMSE) of 1.0496 LAI units.The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD,with an RMSE of 523.0741 mg m-2.The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters,but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.
基金Supported in part by the National Natural Science Foundation of China under Grant No. 11147186Zhejiang Provincial Natural Science Foundation of China under Grant No. LQ12A05004 and Grant from Hangzhou Normal University
文摘We propose a new type of dark energy （DE） model, in which the equation of state of DE wae is a simple function of the fractional energy density Ωde instead of the redshift z. We assume three DE models of this type, and fit them with present observations to get constraints of DE, which are also compared with the CPL model. It is shown that a suitable wda,（Ωde） model can give smaller X2 or smaller errors of wde than that of the CPL model. This new type of DE model can help to study the essential properties and nature of DE.
