Based on the structural characteristics of the double-differenced normal equation, a new method was proposed to resolve the ambiguity float solution through a selection of parameter weights to construct an appropriate...Based on the structural characteristics of the double-differenced normal equation, a new method was proposed to resolve the ambiguity float solution through a selection of parameter weights to construct an appropriate regularized matrix, and a singular decomposition method was used to generate regularization parameters. Numerical test results suggest that the regularized ambiguity float solution is more stable and reliable than the least-squares float solution. The mean square error matrix of the new method possesses a lower correlation than the variancecovariance matrix of the least-squares estimation. The size of the ambiguity search space is reduced and the search efficiency is improved. The success rate of the integer ambiguity searching process is improved significantly when the ambiguity resolution by using constraint equation method is used to determine the correct ambiguity integervector. The ambiguity resolution by using constraint equation method requires an initial input of the ambiguity float solution candidates which are obtained from the LAMBDA method in the new method. In addition, the observation time required to fix reliable integer ambiguities can he significantly reduced.展开更多
Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast a...Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.展开更多
A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This algorithm is the linear combination of th...A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This algorithm is the linear combination of the discrete Conformal mapping(DCM) and the discrete Authalic mapping(DAM). It provides the good properties of both DCM and DAM, such as robustness and low distortion. By adjusting the scaling factor q embedded in the WLSDP, satisfactory parameterizations in different special applications can be achieved.展开更多
WRF(Weather Research and Forecast)模式参数化方案众多,不同参数化方案对降雨模拟效果有较大的影响。为研究WRF模式中云微物理、陆面过程及积云对流参数化方案组合对长江上游地区降雨模拟效果的影响,以长江宜宾至宜昌干流区间为研究区...WRF(Weather Research and Forecast)模式参数化方案众多,不同参数化方案对降雨模拟效果有较大的影响。为研究WRF模式中云微物理、陆面过程及积云对流参数化方案组合对长江上游地区降雨模拟效果的影响,以长江宜宾至宜昌干流区间为研究区域,选取5种云微物理参数化方案、2种陆面过程参数化方案和3种积云对流参数化方案共30种方案组合对该地区4场不同降雨中心落区的典型强降雨过程进行模拟,并以实测站点数据和GPM(Global Precipitation Measurement)降水数据产品为参考,采用TS评分、空报率、漏报率、准确率、平均绝对误差以及均方根误差作为评价指标,充分考虑各指标的不同影响,运用基于熵权的密切值法对降雨模拟结果进行综合评价。结果表明,WRF模式中云微物理WSM3(WRF Single-Moment 3-class)方案,陆面过程Noah(Noah Land Surface Model)方案和积云对流Grell-D(GrellDevenyi Ensemble)方案的参数化方案组合对长江上游地区降雨模拟效果较好,在该参数化方案组合下,WRF模拟的24 h日面雨量平均值的模拟结果与实测资料基本一致,模拟得到的四场典型降雨的24 h面降雨中心和降雨量级分布带均与实际降雨较为接近,大部分地区的模拟误差小于10 mm,且对小雨和中雨的模拟效果更好,此外WRF模拟降雨精度会受地形变化的影响,地形起伏加剧会降低降雨模拟精度,西南山区降雨模拟精度稍低于东北平原地区。研究结果可为流域水文预报提供重要参考。展开更多
Further developments in the hybrid multiscale energy density method are proposed on the basis of our previous papers. The key points are as follows. （i） The theoretical method for the determination of the weight par...Further developments in the hybrid multiscale energy density method are proposed on the basis of our previous papers. The key points are as follows. （i） The theoretical method for the determination of the weight parameter in the energy coupling equation of transition region in multiscale model is given via constructing underdetermined equations. （ii） By applying the developed mathematical method, the weight parameters have been given and used to treat some problems in homogeneous charge density systems, which ,＇ire directly related with multiscale science. （iii） A theoretical algorithm has also been presented for treating non-homogeneous systems of charge density. The key to the theoretical computational methods is the decomposition of the electrostatic energy in the total energy of density functional theory for probing the spanning characteristic at atomic scale, layer by layer, by which the choice of chemical elements and the defect complex effect can be understood deeply. （iv） The＇numerical computational program and design have also been presented.展开更多
The K-multiple-means(KMM)retains the simple and efficient advantages of the K-means algorithm by setting multiple subclasses,and improves its effect on non-convex data sets.And aiming at the problem that it cannot be ...The K-multiple-means(KMM)retains the simple and efficient advantages of the K-means algorithm by setting multiple subclasses,and improves its effect on non-convex data sets.And aiming at the problem that it cannot be applied to the Internet on a multi-view data set,a multi-view K-multiple-means(MKMM)clustering method is proposed in this paper.The new algorithm introduces view weight parameter,reserves the design of setting multiple subclasses,makes the number of clusters as constraint and obtains clusters by solving optimization problem.The new algorithm is compared with some popular multi-view clustering algorithms.The effectiveness of the new algorithm is proved through the analysis of the experimental results.展开更多
文摘Based on the structural characteristics of the double-differenced normal equation, a new method was proposed to resolve the ambiguity float solution through a selection of parameter weights to construct an appropriate regularized matrix, and a singular decomposition method was used to generate regularization parameters. Numerical test results suggest that the regularized ambiguity float solution is more stable and reliable than the least-squares float solution. The mean square error matrix of the new method possesses a lower correlation than the variancecovariance matrix of the least-squares estimation. The size of the ambiguity search space is reduced and the search efficiency is improved. The success rate of the integer ambiguity searching process is improved significantly when the ambiguity resolution by using constraint equation method is used to determine the correct ambiguity integervector. The ambiguity resolution by using constraint equation method requires an initial input of the ambiguity float solution candidates which are obtained from the LAMBDA method in the new method. In addition, the observation time required to fix reliable integer ambiguities can he significantly reduced.
基金Indian Institute of Technology,Kharagpur in India for supporting this work
文摘Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.
文摘A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This algorithm is the linear combination of the discrete Conformal mapping(DCM) and the discrete Authalic mapping(DAM). It provides the good properties of both DCM and DAM, such as robustness and low distortion. By adjusting the scaling factor q embedded in the WLSDP, satisfactory parameterizations in different special applications can be achieved.
文摘WRF(Weather Research and Forecast)模式参数化方案众多,不同参数化方案对降雨模拟效果有较大的影响。为研究WRF模式中云微物理、陆面过程及积云对流参数化方案组合对长江上游地区降雨模拟效果的影响,以长江宜宾至宜昌干流区间为研究区域,选取5种云微物理参数化方案、2种陆面过程参数化方案和3种积云对流参数化方案共30种方案组合对该地区4场不同降雨中心落区的典型强降雨过程进行模拟,并以实测站点数据和GPM(Global Precipitation Measurement)降水数据产品为参考,采用TS评分、空报率、漏报率、准确率、平均绝对误差以及均方根误差作为评价指标,充分考虑各指标的不同影响,运用基于熵权的密切值法对降雨模拟结果进行综合评价。结果表明,WRF模式中云微物理WSM3(WRF Single-Moment 3-class)方案,陆面过程Noah(Noah Land Surface Model)方案和积云对流Grell-D(GrellDevenyi Ensemble)方案的参数化方案组合对长江上游地区降雨模拟效果较好,在该参数化方案组合下,WRF模拟的24 h日面雨量平均值的模拟结果与实测资料基本一致,模拟得到的四场典型降雨的24 h面降雨中心和降雨量级分布带均与实际降雨较为接近,大部分地区的模拟误差小于10 mm,且对小雨和中雨的模拟效果更好,此外WRF模拟降雨精度会受地形变化的影响,地形起伏加剧会降低降雨模拟精度,西南山区降雨模拟精度稍低于东北平原地区。研究结果可为流域水文预报提供重要参考。
基金supported by the National Basic Research Program of China(Grant No.2011CB606402)the National Natural Science Foundation of China(Grant No.51071091)
文摘Further developments in the hybrid multiscale energy density method are proposed on the basis of our previous papers. The key points are as follows. （i） The theoretical method for the determination of the weight parameter in the energy coupling equation of transition region in multiscale model is given via constructing underdetermined equations. （ii） By applying the developed mathematical method, the weight parameters have been given and used to treat some problems in homogeneous charge density systems, which ,＇ire directly related with multiscale science. （iii） A theoretical algorithm has also been presented for treating non-homogeneous systems of charge density. The key to the theoretical computational methods is the decomposition of the electrostatic energy in the total energy of density functional theory for probing the spanning characteristic at atomic scale, layer by layer, by which the choice of chemical elements and the defect complex effect can be understood deeply. （iv） The＇numerical computational program and design have also been presented.
基金National Youth Natural Science Foundationof China(No.61806006)Innovation Program for Graduate of Jiangsu Province(No.KYLX160-781)Project Supported by Jiangsu University Superior Discipline Construction Project。
文摘The K-multiple-means(KMM)retains the simple and efficient advantages of the K-means algorithm by setting multiple subclasses,and improves its effect on non-convex data sets.And aiming at the problem that it cannot be applied to the Internet on a multi-view data set,a multi-view K-multiple-means(MKMM)clustering method is proposed in this paper.The new algorithm introduces view weight parameter,reserves the design of setting multiple subclasses,makes the number of clusters as constraint and obtains clusters by solving optimization problem.The new algorithm is compared with some popular multi-view clustering algorithms.The effectiveness of the new algorithm is proved through the analysis of the experimental results.
