[Objective] The study aimed to explore the degradation law and trend of artificial grassland. [Method] Taking the ryegrass （Lolium perenne） - white clover （ Trifolium repens） artificial grassland in Maiping Townsh...[Objective] The study aimed to explore the degradation law and trend of artificial grassland. [Method] Taking the ryegrass （Lolium perenne） - white clover （ Trifolium repens） artificial grassland in Maiping Township, Guizhou Province as the research object, the grassland vegetation of 40 quadrate from different areas （area around the sheep shed, hilltop, hillside, flatland at the foot of the hill） were analyzed by comparing the dominance and richness index. [ Result] Degradation of different degrees appeared in various areas of this artificial grassland. To be specific, the degradation of grassland around the sheep shed was not serious for less consumption by the sheep; however, the areas on the hilltop and hillside degenerated to the grassland types of dallis grass （ Paspalum dilatatum Poir. ） -Indian lovegrass （ Eragrostis pilosa） and dallis grass - cogongrass [ Imperata cylindrica （ Linn. ） Beauv. ], respectively, and the area at the foot of the hill degenerated to the grassland type dominated by garland chrysanthetnum （ Chrysanthemum coronarium L. ） and knotgrass （ Paspalum distichum L. ）. [ Conclusion ] This study provided a basis for grassland improvement as well as the efficient and sustainable utilization of grazing-type artificial grassland in South China.展开更多
In order to predict the extreme load of the mechanical components during the entire life,an automatic method based on the bootstrapping technology(BT)is proposed to determine the most suitable threshold.Based on all t...In order to predict the extreme load of the mechanical components during the entire life,an automatic method based on the bootstrapping technology(BT)is proposed to determine the most suitable threshold.Based on all the turning points of the load history and a series of thresholds estimated in advance,the generalized Pareto distribution is established to fit the exceedances.The corresponding distribution parameters are estimated with the maximum likelihood method.Then,BT is employed to calculate the mean squared error(MSE)of each estimated threshold based on the exceedances and the specific distribution parameters.Finally,the threshold with the smallest MSE will be the optimal one.Compared to the kurtosis method and the mean excess function method,the average deviation of the probability density function of exceedances determined by BT reduces by 38.52%and 29.25%,respectively.Moreover,the quantile-quantile plot of the exceedances determined by BT is closer to a straight line.The results suggest the improvement of the modeling flexibility and the determined threshold precision.If the exceedances are insufficient,BT will enlarge their amount by resampling to solve the instability problem of the original distribution parameters.展开更多
In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel pr...In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel principal components analysis (SKPCA) feature extraction. Firstly, by fuzzy C-means clustering, some samples are selected from the training sample set to constitute a sample subset. Then, the obtained samples subset is used to execute SKPCA for extracting basic features of the training samples. Finally, using the extracted basic features, the AWNN aerodynamic model is established. The experimental results show that, in 50 times repetitive modeling, the modeling ability of the method proposed is better than that of other six methods. It only needs about half the modeling time of KPCA-AWNN under a close prediction accuracy, and can easily determine the model parameters. This enables it to be effective and feasible to construct the aerodynamic modeling for flight vehicles.展开更多
A spectral calibration technique, a data processing method and the importance of calibration and re-sampling methods for the spectral domain optical coherence tomography system were numerically studied, targeted to op...A spectral calibration technique, a data processing method and the importance of calibration and re-sampling methods for the spectral domain optical coherence tomography system were numerically studied, targeted to optical coherence tomography （OCT） signal processing implementation under graphics processing unit （GPU） architecture. Accurately, assigning the wavelength to each pixel of the detector is of paramount importance to obtain high quality images and increase signal to noise ratio （SNR）. High quality imaging can be achieved by proper calibration methods, here performed by phase calibration and interpolation. SNR was assessed employing two approaches, single spectrum moving window averaging and consecutive spectra data averaging, to investigate the optimized method and factor for background noise reduction. It was demonstrated that the consecutive spectra averaging had better SNR performance.展开更多
基金Supported by National Key Technology R & D Program(2006BAD16B07) Fund of Science and Technology in Guizhou Province ([2008]2074)~~
文摘[Objective] The study aimed to explore the degradation law and trend of artificial grassland. [Method] Taking the ryegrass （Lolium perenne） - white clover （ Trifolium repens） artificial grassland in Maiping Township, Guizhou Province as the research object, the grassland vegetation of 40 quadrate from different areas （area around the sheep shed, hilltop, hillside, flatland at the foot of the hill） were analyzed by comparing the dominance and richness index. [ Result] Degradation of different degrees appeared in various areas of this artificial grassland. To be specific, the degradation of grassland around the sheep shed was not serious for less consumption by the sheep; however, the areas on the hilltop and hillside degenerated to the grassland types of dallis grass （ Paspalum dilatatum Poir. ） -Indian lovegrass （ Eragrostis pilosa） and dallis grass - cogongrass [ Imperata cylindrica （ Linn. ） Beauv. ], respectively, and the area at the foot of the hill degenerated to the grassland type dominated by garland chrysanthetnum （ Chrysanthemum coronarium L. ） and knotgrass （ Paspalum distichum L. ）. [ Conclusion ] This study provided a basis for grassland improvement as well as the efficient and sustainable utilization of grazing-type artificial grassland in South China.
基金The National Science and Technology Pillar Program of China(No.2015BAF07B00)
文摘In order to predict the extreme load of the mechanical components during the entire life,an automatic method based on the bootstrapping technology(BT)is proposed to determine the most suitable threshold.Based on all the turning points of the load history and a series of thresholds estimated in advance,the generalized Pareto distribution is established to fit the exceedances.The corresponding distribution parameters are estimated with the maximum likelihood method.Then,BT is employed to calculate the mean squared error(MSE)of each estimated threshold based on the exceedances and the specific distribution parameters.Finally,the threshold with the smallest MSE will be the optimal one.Compared to the kurtosis method and the mean excess function method,the average deviation of the probability density function of exceedances determined by BT reduces by 38.52%and 29.25%,respectively.Moreover,the quantile-quantile plot of the exceedances determined by BT is closer to a straight line.The results suggest the improvement of the modeling flexibility and the determined threshold precision.If the exceedances are insufficient,BT will enlarge their amount by resampling to solve the instability problem of the original distribution parameters.
基金Project(51209167) supported by Youth Project of the National Natural Science Foundation of ChinaProject(2012JM8026) supported by Shaanxi Provincial Natural Science Foundation, China
文摘In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel principal components analysis (SKPCA) feature extraction. Firstly, by fuzzy C-means clustering, some samples are selected from the training sample set to constitute a sample subset. Then, the obtained samples subset is used to execute SKPCA for extracting basic features of the training samples. Finally, using the extracted basic features, the AWNN aerodynamic model is established. The experimental results show that, in 50 times repetitive modeling, the modeling ability of the method proposed is better than that of other six methods. It only needs about half the modeling time of KPCA-AWNN under a close prediction accuracy, and can easily determine the model parameters. This enables it to be effective and feasible to construct the aerodynamic modeling for flight vehicles.
文摘A spectral calibration technique, a data processing method and the importance of calibration and re-sampling methods for the spectral domain optical coherence tomography system were numerically studied, targeted to optical coherence tomography （OCT） signal processing implementation under graphics processing unit （GPU） architecture. Accurately, assigning the wavelength to each pixel of the detector is of paramount importance to obtain high quality images and increase signal to noise ratio （SNR）. High quality imaging can be achieved by proper calibration methods, here performed by phase calibration and interpolation. SNR was assessed employing two approaches, single spectrum moving window averaging and consecutive spectra data averaging, to investigate the optimized method and factor for background noise reduction. It was demonstrated that the consecutive spectra averaging had better SNR performance.
