DUAL RECIPROCITY HYBRID BOUNDARY NODE METHOD FOR THREE-DIMENSIONAL ELASTICITY WITH BODY FORCE

Combining Dual Reciprocity Method （DRM） with Hybrid Boundary Node Method （HBNM）, the Dual Reciprocity Hybrid Boundary Node Method （DRHBNM） is developed for three-dimensional linear elasticity problems with body force. This method can be used to solve the elasticity problems with body force without domain integral, which is inevitable by HBNM. To demonstrate the versatility and the fast convergence of this method, some numerical examples of 3-D elasticity problems with body forces are examined. The computational results show that the present method is effective and can be widely applied in solving practical engineering problems.     

基于径向基函数神经网络的高光谱遥感图像分类

从径向基函数神经网络的理论出发,针对高光谱数据的特点,设计了有效的特征提取模型,再与径向基函数神经网络的输入层连接,建立了一个新的径向基函数神经网络的高光谱遥感影像分类模型,并用国产OMISII传感器获得的64波段数据进行试验。首先进行了最小噪声分离变换,提取了1～20个分量的数据,使用提取后的数据（20维）、提取后数据的纹理变换（20维）和主成分分析的前（20维）,组成了60维向量数据进行分类处理,这种分类器结构简单、容易训练、收敛速度快,其分类精度达到69.27%,高于BP神经网络分类算法(51.20%)以及常用的最小距离分类（MDC）算法(40.88%)。通过对结果和过程进行分析,实验证明径向基函数神经网络在高光谱遥感分类中具有较好的适用性。     

Numerical Study on an RBF-FD Tangent Plane Based Method for Convection–Diffusion Equations on Anisotropic Evolving Surfaces

In this paper, we present a fully Lagrangian method based on the radial basis function (RBF) finite difference (FD) method for solving convection–diffusion partial differential equations (PDEs) on evolving surfaces. Surface differential operators are discretized by the tangent plane approach using Gaussian RBFs augmented with two-dimensional (2D) polynomials. The main advantage of our method is the simplicity of calculating differentiation weights. Additionally, we couple the method with anisotropic RBFs (ARBFs) to obtain more accurate numerical solutions for the anisotropic growth of surfaces. In the ARBF interpolation, the Euclidean distance is replaced with a suitable metric that matches the anisotropic surface geometry. Therefore, it will lead to a good result on the aspects of stability and accuracy of the RBF-FD method for this type of problem. The performance of this method is shown for various convection–diffusion equations on evolving surfaces, which include the anisotropic growth of surfaces and growth coupled with the solutions of PDEs.     

Structure of ^6He in the frame of a cluster model

A microscopic cluster model with a fully correlated Gaussian basis is developed. In the model, the stochastic variational method is used in order to calculate the ground-energy and the mean-square radius conveniently. Based on this model, the ground-energy level and radius of the neutron halo nucleus, ⁶He, are calculated as a α+n+n three-cluster model. The results are in good agreement with the experimental data.     

STABLE SOLUTION OF TIME DOMAIN INTEGRAL EQUATION METHODS USING QUADRATIC B-SPLINE TEMPORAL BASIS FUNCTIONS

This paper is concerned with stable solutions of time domain integral equation （TDIE） methods for transient scattering problems with 3D conducting objects. We use the quadratic B-spline function as temporal basis functions, which permits both the induced currents and induced charges to be properly approximated in terms of completeness. Because the B-spline function has the least support width among all polynomial basis functions of the same order, the resulting system matrices seem to be the sparsest. The TDIE formula-tions using induced electric polarizations as unknown function are adopted and justified. Numerical results demonstrate that the proposed approach is accurate and efficient, and no late-time instability is observed.     

基于自适应径向基神经网络的类星体光谱自动识别方法

通过对光谱的研究来识别和认证类星体是天文学研究中的重要方法。文章提出了一种对类星体光谱进行自动识别的自适应径向基神经网络(RBFN)方法。该方法包括以下几个步骤: (1)先将训练样本归一化,再利用PCA变换进行降维,获得样本特征向量; (2)设计出K均值聚类算法与梯度下降法相结合的径向基神经网络结构的基本模型,再用SSE(sum of squares error)误差函数进行判断,对RBFN隐含层的神经元进行自动调节,直至满足给定误差阈值; (3)用训练得到的参数对用于测试的样本中的类星体光谱进行识别。该方法不但克服了经典RBFN算法选择隐层神经元数目的困难,而且还提高了对类星体识别的稳定性和正确率。研究结果对于大型光谱巡天所产生的海量数据的自动处理具有重要意义。     

Full four‐component relativistic calculations of the one‐bond 77Se–13C spin‐spin coupling constants in the series of selenium heterocycles and their parent open‐chain selenides

Four‐component relativistic calculations of ⁷⁷Se–¹³C spin–spin coupling constants have been performed in the series of selenium heterocycles and their parent open‐chain selenides. It has been found that relativistic effects play an essential role in the selenium–carbon coupling mechanism and could result in a contribution of as much as 15–25% of the total values of the one‐bond selenium–carbon spin‐spin coupling constants. In the overall contribution of the relativistic effects to the total values of ¹J(Se,C), the scalar relativistic corrections (negative in sign) by far dominate over the spin‐orbit ones (positive in sign), the latter being of less than 5%, as compared to the former (ca 20%). A combination of nonrelativistic second‐order polarization propagator approach (CC2) with the four‐component relativistic density functional theory scheme is recommended as a versatile tool for the calculation of ¹J(Se,C). Solvent effects in the values of ¹J(Se,C) calculated within the polarizable continuum model for the solvents with different dielectric constants (ε 2.2–78.4) are next to negligible decreasing negative ¹J(Se,C) in absolute value by only about 1 Hz. The use of the locally dense basis set approach applied herewith for the calculation of ⁷⁷Se–¹³C spin‐spin coupling constants is fully justified resulting in a dramatic decrease in computational cost with only 0.1–0.2‐Hz loss of accuracy. Copyright © 2014 John Wiley & Sons, Ltd.     

A characterization of nonreflexive banach spaces

D. P. Mil'man and V. D. Mil'man considered sequences of decreasing nonempty closed bounded convex sets with empty intersection to obtain characteristics of non-reflexivity. They showed that in every nonreflexive space there is such a sequence which is ω-separated. We show that in every nonreflexive space there is also always such a sequence which is not ω-separated