灰色理论和BP神经网络在大学生就业信心指数预测中的应用

采用大学生就业信心指数来分析预测其就业信心是值得研究的问题.提出一种灰色理论和BP神经网络相结合的方法对大学生就业信心指数进行预测.首先对影响就业信心的主要因素建立不同的灰色模型,然后将每个灰色模型的预测值作为神经网络的输入,利用神经网络进行组合预测以作为其最终的预测值.结果表明组合模型的预测值相对误差更小,精度更高.     

基于灰色系统理论的多元线性回归分析

运用灰色系统理论剔除了自变量观察数据中的噪声污染,对传统的多元线性回归分析方法进行了改进,建立了灰色多元线性回归分析模型.将模型应用于陕西省就业问题的研究,取得了满意的预测效果.     

农民工城镇就业匹配决策问题研究

伴随城镇化进程的加快,农民工大量涌入城市,如何安置这些农民工、促进其就业,进而实现社会稳定和经济发展已成为政府和学术界迫切需要解决的课题.鉴于此,针对农民工就业匹配问题,利用双边匹配理论,以企业、农民工、政府三方主体满意度最大为目标,构建了农民工城镇就业匹配模型,并以案例验证了模型的有效性与适用性,给出促进农民工城镇就业匹配的对策和建议.     

云南省就业问题的趋势与控制模型研究

基于因果关系理论、因子分析理论、协整分析、自回归分布滞后模型和误差修正模型,对云南省就业问题进行了研究.建立了云南省就业的趋势和控制模型,揭示了云南省就业发展的内在规律及其与各宏观因素之间的系统作用关系.     

轮式移动舞台机器人双模模型预测控制北大核心CSCD

针对轮式移动舞台机器人的快速镇定和移动区域约束控制问题,提出一种快速双模模型预测控制(MPC)算法.考虑轮式移动舞台机器人的位姿约束和速度约束,采用控制Lyapunov函数概念和极坐标系模型设计模型预测控制算法.利用移动舞台机器人与目标的距离、瞄准角和方位角构造一个控制Lyapunov函数,建立移动舞台机器人的一个解析双模结构MPC控制器,再引入自由变量,参数化预测控制变量,降低双模MPC在线优化计算量.在约束条件下,建立了轮式移动舞台机器人闭环系统稳定性和MPC递推可行性理论结果.最后,通过与常规MPC比较,仿真验证所提算法的有效性和优越性.     

轮式移动舞台机器人双模模型预测控制

针对轮式移动舞台机器人的快速镇定和移动区域约束控制问题,提出一种快速双模模型预测控制(MPC)算法.考虑轮式移动舞台机器人的位姿约束和速度约束,采用控制Lyapunov函数概念和极坐标系模型设计模型预测控制算法.利用移动舞台机器人与目标的距离、瞄准角和方位角构造一个控制Lyapunov函数,建立移动舞台机器人的一个解析双模结构MPC控制器,再引入自由变量,参数化预测控制变量,降低双模MPC在线优化计算量.在约束条件下,建立了轮式移动舞台机器人闭环系统稳定性和MPC递推可行性理论结果.最后,通过与常规MPC比较,仿真验证所提算法的有效性和优越性.     

我国就业人数的数学模型探析及前景预测

基于经济学理论和逐步回归分析方法优选影响就业较大的9个指标,建立了城镇就业人口数与该9个指标之间的数学模型.针对建筑、交通运输行业,东部、西部地区以及不同学历问题,建立了城镇就业人数的较精确数学模型.考虑国家宏观调控政策的影响,利用灰色模型和非线性回归模型优选预测2009年及2010年上半年的就业前景.最后,对提高我国城镇就业人口数提出相关建议.     

粒子群优化的收敛分析及在广义预测控制中的应用

在进行粒子群优化的收敛性理论分析的基础上,推出了保证粒子群优化算法收敛性的参数设置区域,合理选择粒子群算法的关键参数,将粒子群优化与广义预测控制有机融合,用粒子群算法来解决广义预测控制的优化问题,提出基于粒子群优化的广义预测控制算法,通过工业过程对象的仿真并和传统的广义预测控制算法进行了对比分析,表明了该算法的有效性,特别是算法具有良好的输出跟踪精度和较强的鲁棒性.     

复杂系统视角下的地方政府行政编制规模影响因素系统分析——基于DEMATEL-ISM集成方法

地方政府行政编制规模影响因素的研究是行政编制总量控制及结构调整的基础.在系统理科学论指导下,运用文献研究与实地调研结合方法,从经济、社会、政治等角度寻找出了影响地方政府行政编制规模的25个影响因素.利用Delphi法,在25个因素中识别出了10个重要因素.在10个重要因素基础上,进一步利用系统工程中的DEMATEL-ISM集成方法分析重要因素的系统结构,对重要因素进行层次化和结构化,建立了地方政府公共就业规模影响因素5级递阶结构模型,找到了影响地方政府行政编制规模的根源因素及影响机制.研究结果对地方政府行政编制规模地合理确定、总量地有效控制具有理论参考价值.     

基于灰色马尔可夫模型的物流配送需求量预测研究

研究可以较准确地预测物流配送需求量的数学模型,以服务于政府及企业的物流规划及其决策.将灰色理论和离散状态的马尔可夫链相结合,用灰色马尔可夫链对物流配送需求量进行实证研究.针对灰色数据系列首先用GM模型进行趋势预测,然后利用马尔可夫状态转移概率矩阵预报方法对其预测值进行二次拟合,预测精度明显高于GM模型预测.     

Asymptotic ordination of artificial satellite Hamiltonian

Spatial Agencies’ projects for future artificial satellites continue to grow in number and complexity. These projects need the development of analytical theories in order to place the satellites in the most suitable orbit. The most common technique for constructing analytical theories is the Lie–Deprit method, which requires to expand in series of a small parameter the Hamiltonian of the problem. This expansion is not trivial but, usually, it is made without care. In this paper we provide a unified and systematic framework to get that development in a rigorous way.     

Fast sensitivity analysis of defective system

Sensitivity analysis of linear vibration system is of wide interest. In this paper, sensitivity analysis based on non-defective system and defective system is summarized in all cases. Specially, for the defective systems, a fast method for the perturbation problem of state vectors is constructed in terms of the theories of generalized eigenvectors and adjoint matrices. By this method, the state vector derivatives can be expressed by a linear combination of generalized eigenvectors. The expansion coefficients can be obtained without solving large-scale equations based on eigensolutions of original system. Numerical results demonstrate the effectiveness and the stability of the method.     

Remarks on generic stability in independent theories

In NIP theories, generically stable Keisler measures can be characterized in several ways. We analyze these various forms of “generic stability” in arbitrary theories. Among other things, we show that the standard definition of generic stability for types coincides with the notion of a frequency interpretation measure. We also give combinatorial examples of types in NSOP theories that are finitely approximated but not generically stable, as well as ϕ-types in simple theories that are definable and finitely satisfiable in a small model, but not finitely approximated. Our proofs demonstrate interesting connections to classical results from Ramsey theory for finite graphs and hypergraphs.     

EXISTENCE OF FORECAST AND DECISION HORIZONS FOR OPTIMAL CONTROL PROBLEMS OF NONLINEAR SYSTEMS

ＥＸＩＳＴＥＮＣＥＯＦＦＯＲＥＣＡＳＴＡＮＤＤＥＣＩＳＩＯＮＨＯＲＩＺＯＮＳＦＯＲＯＰＴＩＭＡＬＣＯＮＴＲＯＬＰＲＯＢＬＥＭＳＯＦＮＯＮＬＩＮＥＡＲＳＹＳＴＥＭＳ￥ＺｈａｎｇＣｈｅｎｇｙｕｎ（张成云）（ＦｕｄａｎＵｎｉｖｅｒｓｉｔｙ，复旦大学，邮编：...     

A weighted causal theory for acquiring and utilizing open knowledge

Motivated by enabling intelligent robots/agents to take advantage of open-source knowledge resources to solve open-ended tasks, a weighted causal theory is introduced as the formal basis for the development of these robots/agents. The action model of a robot/agent is specified as a causal theory following McCain and Turner's nonmonotonic causal theories. New knowledge is needed when the robot/agent is given a user task that cannot be accomplished only with the action model. This problem is cast as a variant of abduction, that is, to find the most suitable set of causal rules from open-source knowledge resources, so that a plan for accomplishing the task can be computed using the action model together with the acquired knowledge. The core part of our theory is constructed based on credulous reasoning and the complexity of corresponding abductive reasoning is analyzed. The entire theory is established by adding weights to hypothetical causal rules and using them to compare competing explanations which induce causal models satisfying the task. Moreover, we sketch a model theoretic semantics for the weighted causal theory and present an algorithm for computing a weighted-abductive explanation. An application of the techniques proposed in this paper is illustrated in an example on our service robot, KeJia, in which the robot tries to acquire proper knowledge from OMICS, a large-scale open-source knowledge resource, and solve new tasks with the knowledge.     

On dividing chains in simple theories

Dividing chains have been used as conditions to isolate adequate subclasses of simple theories. In the first part of this paper we present an introduction to the area. We give an overview on fundamental notions and present proofs of some of the basic and well-known facts related to dividing chains in simple theories. In the second part we discuss various characterizations of the subclass of low theories. Our main theorem generalizes and slightly extends a well-known fact about the connection between dividing chains and Morley sequences (in our case: independent sequences). Moreover, we are able to give a proof that is shorter than the original one. This result motivates us to introduce a special property of formulas concerning independent dividing chains: For any dividing chain there exists an independent dividing chain of the same length. We study this property in the context of low, short and ω -categorical simple theories, outline some examples and define subclasses of low and short theories, which imply this property. The results give rise to further studies of the relationships between some subclasses of simple theories. Research supported by CNPq grant 150309/2003-1. Research supported by CNPq grant 304365/2003-3 (Modelos, Provas e Algoritmos)     

Unbounded connected component of the positive solution set of nonlinear operator equation and its applications

In this paper, by using global bifurcation theories we obtain some results for structure of positive solution set of some nonlinear equations with parameters. As a result, we obtain some existence results for positive solutions of the nonlinear operator equation. The main result can be applied to various of differential boundary value problems to obtain the existence results for positive solutions without the assumption that the nonlinearities are positone.