基于协同创新理念的高校研究生党建工作模式的研究

传统的高校研究生党建工作模式因自身的不适应性在新时期面临重重困境,协同创新理念已经成为当今高校探索资源共享新型研究生党建工作模式的必然选择。本文从理念、战略、利益三方面阐述对协同创新理念下研究生党建工作和思想政治教育的研究,并从构建校园网络平台、加强研本互动、完善交流机制三个具体措施表达了对协同创新理念推动研究生党建工作创新的理解。     

协同设计中的应用共享技术研究

文章针对目前应用共享的国内外研究现状,从应用共享的原理入手,对应用共享的一个核心问题--共享机制以及按共享机制的分类进行了分析和研究,进而讨论了应用共享的实现过程所涉及到应用共享实现方法.并通过协同设计工具及系统的开发对实现应用共享过程中遇到的问题,提出了一些相对较优的解决办法.     

基于有向网络的一致性跟踪算法

研究了leader有控制输入且followers未知该输入条件下的线性多智能 体一致性跟踪问题.提出两种一致性跟踪算法,证明两种算法在leader到followers存在一棵 有向生成树且follower间拓扑是有向条件下,网络就能跟踪leader的状态.对于第一种算法,节点根 据相邻节点或leader的状态来求解其控制输入,并基于代数Riccati不等式给出 连续情形下算法稳定性条件.第二种算法直接利用相邻节点或leader的状态,使followers在上述网络条件下跟踪leader的状态,同样基于代数Riccati不等式给出算法稳定性条件. 仿真结果验证了算法的有效性.     

基于集散式模型预测控制的多无人机协同分区搜索

针对多无人机在对大范围目标区域执行协同搜索任务时搜索资源分配不均、容易因频繁转场造成资源浪费等问题,借鉴集中式控制和分布式控制结构的优点,建立了集散式多无人机(unmanned aerial vehicle,UAV)协同搜索结构体系,通过聚类分析和V图划分等方法对目标区域进行分区,结合各子区域任务特点对无人机群进行搜索任务分配,并采用一种经改进后可有效增大UAV预测范围的预测控制模型,研究了动态环境下多UAV集散式协同分区搜索问题,最后,将所提方法与常见几种协同搜索方法进行对比仿真,获取仿真结果验证了所提方法在目标发现概率和搜索效率方面的有效性和优越性.     

高校科研能力的协同IWD粗糙集-块神经网络评估模型

针对高校科研能力评估过程中存在的多因素、高非线性特点,经典评估模型主观性较强,导致模型评估准确性不高的问题,提出基于协同智能水滴算法IWD和粗糙集块神经网络RBNN的高校科研能力评估模型。首先,引入智能水滴算法,并针对传统智能水滴算法固定旁域搜索范围不利于提升算法搜索效率的问题,提出一种局部空间自动缩放算法LSAS,该算法根据当前种群最优个体,自动调整下一步搜索空间大小,对进化过程进行指导,提高算法的进化效率;其次,基于粗糙集理论对高校科研能力数据进行特征预处理,简化数据计算量;最后,对块神经网络和粗糙集参数进行编码,并对高校科研能力模型进行评估。仿真结果表明,此评估模型具有较高的准确性和较快的计算效率。     

Exponential synchronization of nonlinear multi‐agent systems with time delays and impulsive disturbances

The problem of cooperative synchronization of nonlinear multi‐agent systems with time delays is investigated in this paper. Compared with the existing works about synchronization (or consensus) of multi‐agent systems, the method in this paper provides a more general framework by considering nonlinear multi‐agent systems with time delays and impulsive disturbances. The model in this paper is sufficiently general to include a class of delayed chaotic systems. Based on the Lyapunov stability theory and algebraic graph theory, sufficient conditions are presented to guarantee the cooperative exponential synchronization for these multi‐agent delayed nonlinear systems. These conditions are expressed in terms of linear matrix inequalities, which can easily be checked by existing software tools. It is seen that the Lyapunov functions must be constructed based on the graph topology to prove synchronization. The well‐known master–slave (drive‐response) synchronization of two chaotic delayed systems is a special case of this paper, and therefore, the results in this paper are also useful for practical applications in secure communication. Simulation results verify the effectiveness of the proposed synchronization control algorithm. Copyright © 2015 John Wiley & Sons, Ltd.     

Game‐Based Valley‐Fill Charging Coordination for Large‐Population Plug‐in Electric Vehicles

Charging coordination of large‐population autonomous plug‐in electric vehicles (PEVs) in the power grid can be formulated as a class of constrained optimization problems. To overcome the computational complexity, a game‐based method is proposed for the charging problems of the PEV population, which is composed of homogeneous subpopulations, such that individuals update their best charging strategies simultaneously with respect to a common electricity price determined by the total demand. To mitigate the oscillation behavior caused by the greedy behavior for the cheap electricity by individuals, a deviation cost is introduced to penalize against the deviation of the individual strategy from the average value of the homogeneous subpopulation. By adopting a proper deviation cost and following a best strategy update mechanism, the game systems may converge to the socially optimal valley‐fill Nash equilibrium. Simulation examples are studied to illustrate the results.     

自主-合作教学模式在C＋＋程序设计教学改革中的应用

针对在C＋＋程序设计课程教学中存在的问题,结合对自主-合作教学模式的研究,提出以自主学习教学模式贯穿教学始终;案例驱动的精讲与泛读相结合;手写程序与机器调试相结合;自主学习与合作学习相结合的教学新思路。并阐述了上述方法在教学改革实践中的具体应用及效果。     

Joint relay selection and power allocation for amplify-and-forward two-path relaying networks

This paper presents a joint relay selection and power allocation scheme for amplify-and-forward two-path relaying networks,in which diferent relay nodes forward information symbols alternatively in adjacent time slots.Our approach is based on the maximization of the received signal-to-noise ratio under total power consumption by the transmission of the symbol.We show that in spite of inter-relay interferences,the maximization problem has a closed-form solution.Simulation results explicitly indicate that the performance of proposed approach outmatches the existing methods including equal power allocation and one-path relaying.     

A suboptimal joint bandwidth and power allocation for cooperative relay networks＂ a cooperative game theoretic approach

In commercial networks, user nodes operating on batteries are assumed to be selfish to consume their resources (i.e., bandwidth and power) solely maximizing their own benefits (e.g., the received signal-to-noise ratios (SNRs) and datarates). In this paper, a cooperative game theoretical framework is proposed to jointly perform the bandwidth and power allocation for selfish cooperative relay networks. To ensure a fair and efficient resource sharing between two selfish user nodes, we assume that either node can act as a source as well as a potential relay for each other and either node is willing to seek cooperative relaying only if the datarate achieved through cooperation is not lower than that achieved through noncooperation (i.e., direct transmission) by consuming the same amount of bandwidth and power resource. Define the cooperative strategy of a node as the number of bandwidth and power that it is willing to contribute for relaying purpose. The two node joint bandwidth and power allocation (JBPA) problem can then be formulated as a cooperative game. Since the Nash bargaining solution (NBS) to the JBPA game (JBPAG) is computationally difficult to obtain, we divide it into two subgames, i.e., the bandwidth allocation game (BAG) and the power allocation game (PAG). We prove that both the subgames have unique NBS. And then the suboptimal NBS to the JBPAG can be achieved by solving the BAG and PAG sequentially. Simulation results show that the proposed cooperative game scheme is efficient in that the performance loss of the NBS result to that of the maximal overall data-rate scheme is small while the maximal-rate scheme is unfair. The simulation results also show that the NBS result is fair in that both nodes could experience better performance than they work independently and the degree of cooperation of a node only depends on how much contribution its partner can make to improve its own performance.