向量多项式优化问题的数值方法

向量多项式优化问题中的目标函数和约束条件都是由多项式描述的.先将多目标多项式函数分别通过主要目标法、线性加权和法和理想点法等转化为单目标多项式函数,再利用Lasserre松弛方法求解该多项式优化问题,从而得到原向量多项式优化问题的弱有效解或有效解.数值实验结果表明该数值方法是有效的.     

同行评议学术图书内容的质量控制--GPRC标签

GPRC质量标签是用于保证同行评议图书内容质量的标志。该标签增强了学术图书出版的透明度和学术性，对于社会科学和人文学科的图书审核和出版以及高校研究项目的科技成果鉴定有着重要保障作用。介绍了学术图书同行评议的形式与内容，阐述了GPRC质量标签的产生背景及其实施与发展，讨论了与GPRC标签相关的问题，包括内容质量标签的重要性以及GPRC标签的利益动机。     

“数字城管”外业普查与建库的质量控制

以某市"数字城管"外业普查与建库项目为背景,重点探讨了项目实施过程中各个阶段的质量控制要点。     

基于值域博弈的主动悬架系统H_∞可拓控制

建立7自由度整车主动悬架系统模型,并设计H_∞控制器。在此基础上,选取特征量,划分三种不同的值域,经过关联函数计算,建立其H_∞可拓控制器;在不同方案下以经典域和可拓域为博弈双方构造博弈矩阵,获得值域划分纳什平衡点,采用模糊控制规则动态整定可拓域和经典域边界,优化悬架H_∞可拓控制系统的控制性能。最后利用MATLAB/Simulink软件进行仿真,并对其仿真结果进行比较.仿真结果表明,H_∞可拓控制较H_∞控制能更好地改善主动悬架性能,而通过值域博弈的H_∞可拓控制器进一步提高了悬架系统的控制性能。     

万家寨引黄工程南一泵站通风系统触摸屏改造

介绍了山西省万家寨引黄工程南一泵站通风系统的组成及结构,从硬件选择和软件开发等方面对南一泵站通风系统控制屏改造进行了阐述和分析,给出了同类站点控制系统改造升级的解决方案。     

房地产建安工程成本控制措施浅谈

房地产建安工程成本是房地产成本管理的重要工作,实现开发利润最大化的主要措施之一。论文根据房地产建安工程成本控制的实际经验,总结了成本控制的具体措施及方法。     

特征值在高等代数中的作用

以高等代数中的定义、定理和例题为依据,论述了特征值具有化繁为简的作用,它还是实对称矩阵和二次型的本质所在.特别地,它是解决许多代数问题的重要工具.     

基于摄像头的直立行走智能车控制系统设计

针对以往靠中心线提取速度较慢导致车模方向控制不稳,容易跑出赛道等问题,设计以K60微控制器为核心控制单元,利用CMOS摄像头对路径信息进行采集,在提取赛道边界和控制车体方向时创新性的使用了"窗口检测法"和"双比例"PD控制方法。"窗口检测法"能够缩短赛道边界的提取时间,提高搜索效率。双比例PD控制能够对比例参数P进行实时调整,进而更及时、准确地控制车模的运行方向。     

Ground demonstration system based on in-orbit assembly oriented manipulator flexible force control

To eliminate the load weight limit of carrier rockets and reduce the burden on support struc-tures,in-orbit assembly is a key technology to make design of scattering a large diameter telescope into submirror modules, which requires smooth operation of assembly robots, and flexible force con-trol technology is necessary.A ground demonstration system is presented for in-orbit assembly focu-sing on flexible force control.A six-dimensional force/torque sensor and its data acquisition system are used to compensate for gravity.For translation and rotation, an algorithm for flexible control is proposed.A ground transportation demonstration verifies accuracy and smoothness of flexible force control, and the transportation and assembly task is completed automatically.The proposed system is suitable for the development of in-orbit assembly robots.     

LEARNING CAUSAL GRAPHS OF NONLINEAR STRUCTURAL VECTOR AUTOREGRESSIVE MODEL USING INFORMATION THEORY CRITERIA

Detection and clarification of cause-effect relationships among variables is an important problem in time series analysis. Traditional causality inference methods have a salient limitation that the model must be linear and with Gaussian noise. Although additive model regression can effectively infer the nonlinear causal relationships of additive nonlinear time series, it suffers from the limitation that contemporaneous causal relationships of variables must be linear and not always valid to test conditional independence relations. This paper provides a nonparametric method that employs both mutual information and conditional mutual information to identify causal structure of a class of nonlinear time series models, which extends the additive nonlinear times series to nonlinear structural vector autoregressive models. An algorithm is developed to learn the contemporaneous and the lagged causal relationships of variables. Simulations demonstrate the effectiveness of the nroosed method.