基于VRML-JAVA的可视化装配及其原型系统实现

提出了一种新型的Web环境下3D交互仿真结构。系统采用基于VRML-JAVA的虚拟现实技术,3D模型下载到客户端显示,复杂的运算和仿真在服务器上运行,这种方式可以提高系统的扩展性并降低对客户端软硬件条件的要求。文中对该结构在可视化装配中的应用进行了研究并介绍了其中的关键技术以及原型系统的实现。     

判断矩阵凸组合系数的优化原理研究

对判断矩阵凸组系数的优化原理进行了研究 ,给出了判断矩阵最优凸组合系数的求解方法 ,讨论了判断矩阵最优凸组合的性质.     

住宅市场需求的组合预测

将组合预测方法引入住宅市场需求预测,以实例具体介绍了组合预测的应用过程,实例中采用了神经网络、灰色模型等预测方法的组合体系,对当前环境下的住宅市场需求预测进行了有益的探索。     

随机需求下基于库存责任期的装配系统准时供货模型

以装配系统为研究对象, 考虑在VMI模式下, 当制造商采取设定库存责任期以抵御市场需求时间不确定的风险时, 供应商的最优供货时间决策和制造商最优的库存责任期设置. 文章分别建立了单供应商对单制造商和多供应商对单制造商的主从博弈准时供货模型, 通过数学证明和遍历算法找到了供应链双方在不同模式下的最优选择. 研究结果证明制造商并 不应该选择过长的库存责任期, 而供应商之间的不同步供货会对供应链整体造成巨大损失. 并且通过对比集中与分散决策下的供应链绩效, 给出实现系统协同的必要条件. 最后通过算例分析进一步证明相关结论.     

烟机卷接机组中AMK交流伺服系统的硬件组成及性能分析

AMK交流伺服系统在卷接机组中的应用主要是代替传统的由主电机、齿轮和皮带的传动方式,实现多电机同步驱动。本文重点介绍AMK交流伺服系统在卷接机组中的硬件组成,并对其性能加以分析。     

基于动态组合残差修正的预测方法

本文建立了一种基于残差修正的组合预测方法,并基于该方法证明了针对多个单一的预测方法根据其在某个时间段的相对预测误差的大小选择组合选项可以进一步提高预测精度.提出了针对不同时间段可根据各种单项预测模型的相对预测误差的大小动态选取相对预测误差最小的两种模型构成组合残差来修正基本方法的预测误差,以提高预测精度.最后通过实际空调负荷预测对其进行了验证,结果表明这种动态组合残差修正的预测方法相对于基于多个固定单一预测方法的组合预测方法,可以进一步改善预测效果.     

The impact of parameter and model uncertainty on market risk predictions from GARCH‐type models

We study the effect of parameter and model uncertainty on the left‐tail of predictive densities and in particular on VaR forecasts. To this end, we evaluate the predictive performance of several GARCH‐type models estimated via Bayesian and maximum likelihood techniques. In addition to individual models, several combination methods are considered, such as Bayesian model averaging and (censored) optimal pooling for linear, log or beta linear pools. Daily returns for a set of stock market indexes are predicted over about 13 years from the early 2000s. We find that Bayesian predictive densities improve the VaR backtest at the 1% risk level for single models and for linear and log pools. We also find that the robust VaR backtest exhibited by linear and log pools is better than the backtest of single models at the 5% risk level. Finally, the equally weighted linear pool of Bayesian predictives tends to be the best VaR forecaster in a set of 42 forecasting techniques.     

体域网中基于特征组合的步态行为识别

物联网(internet of things,IOT)拥有无处不在的识别、传感和通信能力,体域网(body area network,BAN)属于物联网中和人体相关的领域,其应用广泛,可以在日常生活中对人们进行监测及提供帮助.行走是许多日常活动的基本环节,因而步态分析能为体域网应用提供重要的生理行为信息.现有的步态分析已取得一定的研究成果,但仍存在一些问题,例如大多数步态特征提取是对加速度信号进行6重以上的变换,使得特征达到了45维以上,最后需要通过降维或优化来简化特征,较为复杂.本文设计一种灵活便捷的数据采集系统,并利用小波变换、傅里叶变换和四分位差提取出加速度信号中比较简单、低维度但能反应运动特征的步态参数,之后通过模式识别算法进行步态行为识别验证.实验结果表明该系统使用方便,特征提取方法简单实用,识别精确度为97%,EER(equal error rate)最小可到0.9%.     

Forecast Combination and Bayesian Model Averaging: A Prior Sensitivity Analysis

In this study we evaluate the forecast performance of model‐averaged forecasts based on the predictive likelihood carrying out a prior sensitivity analysis regarding Zellner's g prior. The main results are fourfold. First, the predictive likelihood does always better than the traditionally employed ‘marginal’ likelihood in settings where the true model is not part of the model space. Secondly, forecast accuracy as measured by the root mean square error (RMSE) is maximized for the median probability model. On the other hand, model averaging excels in predicting direction of changes. Lastly, g should be set according to Laud and Ibrahim (1995: Predictive model selection. Journal of the Royal Statistical Society B 57 : 247–262) with a hold‐out sample size of 25% to minimize the RMSE (median model) and 75% to optimize direction of change forecasts (model averaging). We finally apply the aforementioned recommendations to forecast the monthly industrial production output of six countries, beating for almost all countries the AR(1) benchmark model. Copyright © 2011 John Wiley & Sons, Ltd.     

Revision of the genus Mimopodabrus Wittmer (Coleoptera,Cantharidae)

The genus Mimopodabrus Wittmer is reviewed, and the genus diagnosis is re-described. Three new species are described, M. multidentatus sp. nov. (Guangdong, China), M. variabilis sp. nov. (Yunnan, China) and M. diversefoveolatus sp. nov. (Lao Cai, Vietnam), with illustrations of habitus, antennae and aedeagus. A species is transferred from Micropodabrus to this genus, M. bicoloriceps (Wittmer, 1989 Wittmer, W. 1989. 42. Beitrag zur Kenntnis der indo-malaiischen Cantharidae und Malachiidae (Coleoptera). Entomol Basil., 13: 209–237.  [Google Scholar]) comb. nov. A species is synonymized, M. bicoloriceps (Wittmer, 1989 Wittmer, W. 1989. 42. Beitrag zur Kenntnis der indo-malaiischen Cantharidae und Malachiidae (Coleoptera). Entomol Basil., 13: 209–237.  [Google Scholar]) comb. nov.?=?M. bicoloriceps Wittmer, 1997 syn. nov. and the definition of M. yunnanus (Wittmer, 1993 Wittmer, W. 1993. Zur Kenntnis der palaearktischen und indo-malaiischen Cantharidae (Coleoptera). Entomol Basil., 16: 203–253.  [Google Scholar]) is restricted. A key to all known species of this genus is provided.