从三个角度考察柯西不等式

柯西不等式是高等数学中的重要不等式,它在解析几何、数学分析与高等代数这3门数学专业主干基础课程中均有渗透.从这3门课程的角度,分别给出柯西不等式的不同形式和证明过程,并简要地阐述它们的联系,最后做出小结.     

关于二面体群的共轭类长素图

讨论二面体群的结构问题,利用GAP软件给出二面体群D2n的共轭类长素图,并完整给出当n以及n/2分别是奇数和偶数时的共轭类长素图情况.     

城乡公共服务均等化现状与对策——以安徽省为例

城乡公共服务均等化是市场经济基本原则的要求,同时也是我国市场经济深入发展提出的新问题。财政资源配置不当可能是导致城乡公共服务非均等的主要原因。通过对安徽省城乡公共服务均等化现状的研究,有助于提出更有针对性的改进措施,同时也将对该地区经济和社会发展起到一定的推动作用。     

我国SNS营销现状与发展趋势研究

从SNS营销内涵、营销工具、营销策略和营销评价等方面对有代表性的文献成果进行了分析,揭示了我国SNS营销的研究进展,探讨了我国SNS营销的发展趋势,包括SNS营销认识动态化、商务智能方法和社交平台结合深入化、营销策略微观化、评价思路多元化.     

A Layer-Stripping Method for 3D Near-Surface Velocity Model Building Using Seismic First-Arrival Times

In order to improve the efficiency of 3D near-surface velocity model building, we develop a layer-stripping method using seismic first-arrival times. The velocity model within a Common Mid-Point (CMP) ...     

基于改进灰狼算法优化SVR的航天侦察装备效能评估

定量评估航天侦察装备效能是武器装备体系建设的重要环节之一, 对装备发展和作战应用具有重要的现实意义。针对评估样本数据少、效能在多指标因素影响下变化规律非线性等条件下的效能评估问题, 提出一种基于改进灰狼(improved grey wolf optimizer, IGWO)算法优化的支持向量回归机(support vector regression, SVR)评估方法(IGWO-SVR)。引入反向学习策略及余弦非线性收敛因子改进灰狼优化算法收敛性能及全局寻优能力, 并将其应用于基于支持SVR效能评估参数的优化。基于航天侦察装备特点, 构建评估指标体系及航天侦察装备效能评估模型。最后, 通过对一定作战想定背景下航天侦察装备效能进行仿真评估, 验证了所提方法的合理性及优化模型的有效性。     

An Economic Model-Based Matching Approach Between Buyers and Sellers Through a Broker in an Open E-Marketplace

A broker in an open e-marketplace enables buyers and sellers to do business with each other. Although a broker plays an important role in e-marketplaces, theory and guidelines for matching between buyers and sellers in multi-attribute exchanges are limited. Therefore, a challenge for a broker’s responsibility is how to maximize a buyer’s total satisfaction degree as its goals under the consideration of trade-off between a buyer’s buying quantity and price paid to a seller, and other attributes. To solve this challenge, this paper proposes an economic model-based matching approach between a buyer’s requirements and a seller’s offers. The major contributions of this paper are that (i) a broker can model a seller’s price policy as per a buyer’s buying quantity through communication between a broker and a seller; (ii) due to each buyer’s different quantity demand, a broker models a buyer’s satisfaction degree as per a buyer’s buying quantity based on communication between a broker and a buyer; and (iii) to carry out a broker’s matching processes, an objective function and a set of constraints are generated to help a broker to maximize a buyer’s total satisfaction degree. Experimental results demonstrate the good performance of the proposed approach.     

基于数据场联合PRI变换与聚类的雷达信号分选

基于脉冲描述字进行雷达信号分选时,传统聚类算法需要预先人工设定聚类中心和聚类数目。针对该问题,提出一种基于数据场理论联合脉冲重复间隔(pulse repetition interval,PRI)变换与聚类的雷达信号分选新方法。首先,依据数据场理论,基于势值大小实现干扰点剔除,而后利用PRI变换算法进行PRI估计,依据PRI估计值将归一化脉冲描述字数据预分类,进而以各类数据集中心间的欧氏距离小于辐射因子为准则进行类别合并,自动得到初始聚类中心和聚类数目,最后通过改进K-Means算法完成聚类分选。仿真实验表明:所提方法能够应对存在频率捷变,重频参差、抖动、参数交叠、局部脉冲丢失的复杂信号环境,分选正确率明显提升。     

Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks

Random walks are a standard tool for modeling the spreading process in social and biological systems.But in the face of large-scale networks,to achieve convergence,iterative calculation of the transition matrix in random walk methods consumes a lot of time.In this paper,we propose a three-stage hierarchical community detection algorithm based on Partial Matrix Approximation Convergence(PMAC) using random walks.First,this algorithm identifies the initial core nodes in a network by classical measurement and then utilizes the error function of the partial transition matrix convergence of the core nodes to determine the number of random walks steps.As such,the PMAC of the core nodes replaces the final convergence of all the nodes in the whole matrix.Finally,based on the approximation convergence transition matrix,we cluster the communities around core nodes and use a closeness index to merge two communities.By recursively repeating the process,a dendrogram of the communities is eventually constructed.We validated the performance of the PMAC by comparing its results with those of two representative methods for three real-world networks with different scales.