Real‐Time Forecasts of Inflation: The Role of Financial Variables

We present a mixed‐frequency model for daily forecasts of euro area inflation. The model combines a monthly index of core inflation with daily data from financial markets; estimates are carried out with the MIDAS regression approach. The forecasting ability of the model in real time is compared with that of standard VARs and of daily quotes of economic derivatives on euro area inflation. We find that the inclusion of daily variables helps to reduce forecast errors with respect to models that consider only monthly variables. The mixed‐frequency model also displays superior predictive performance with respect to forecasts solely based on economic derivatives. Copyright © 2012 John Wiley & Sons, Ltd.     

Backward‐in‐Time Selection of the Order of Dynamic Regression Prediction Model

We investigate the optimal structure of dynamic regression models used in multivariate time series prediction and propose a scheme to form the lagged variable structure called Backward‐in‐Time Selection (BTS), which takes into account feedback and multicollinearity, often present in multivariate time series. We compare BTS to other known methods, also in conjunction with regularization techniques used for the estimation of model parameters, namely principal components, partial least squares and ridge regression estimation. The predictive efficiency of the different models is assessed by means of Monte Carlo simulations for different settings of feedback and multicollinearity. The results show that BTS has consistently good prediction performance, while other popular methods have varying and often inferior performance. The prediction performance of BTS was also found the best when tested on human electroencephalograms of an epileptic seizure, and for the prediction of returns of indices of world financial markets.Copyright © 2013 John Wiley & Sons, Ltd.     

轧机机架的动态特性仿真与结构优化

应用有限元分析方法,对某铝带二辊轧机机架装配系统进行了动态特性仿真,得出了固有频率和振型的变化规律.针对轧机机架的薄弱环节,通过参数化方法进行灵敏度分析和结构优化设计,使系统的动态特性得到提高,该结论为高性能轧机的设计优化,提供了一定的参考.     

一种用于动态光散射测量的虚拟数字相关仪

根据数字相关的基本原理, 利用高速数据采集卡和实验室虚拟仪器工程平台LabVIEW, 设计开发用于动态光散射测量的数字相关仪. 利用该数字相关仪对动态光散射实测数据进行分析处理, 给出散射光强的时间自相关函数曲线, 反演计算了颗粒粒度, 并与已知粒度进行比较, 得到较好的测试结果.      

Cu-Cr-Zr-Ag合金高温流变行为及织构演化研究

采用Gleeble-1500D热模拟试验机对Cu-Cr-Zr-Ag合金进行热压缩试验,研究了Cu-Cr-Zr-Ag合金在不同应变速率和变形温度的流变应力行为、微观组织演变和动态再结晶机制,利用光学显微镜(OM)研究了Cu-Cr-Zr-Ag合金的压缩速率、形变温度对合金微观织构的影响.结果表明:在压缩速率为0.001~10 s^-1的区间内,Cu-Cr-Zr-Ag合金存在近稳态流变特征,即流变应力随温升及压缩速率的降低而变小.形变温度越高,越能促使再结晶形核,压缩速率越低,越利于动态再结晶充分发生.     

基于ADAMS.LifeMOD的人体头颈部动力学仿真与验证

基于多刚体动力学软件ADAMS和生物力学仿真软件LifeMOD,建立了一个人体头颈部三维多刚体动力学模型。该模型包括颅骨、颈椎骨、肩胛骨、躯干上段以及体现粘弹性性质的肌肉组织。采用美国海军力学实验室的前碰撞志愿者实验数据对模型进行了验证。验证结果表明,该模型具有很好的可信度,可以用来研究在碰撞条件下头颈部的动力学响应特性。     

面向多目标的自适应动态概率粒子群优化算法

将基于动态概率搜索的粒子群优化(Particle swarm optimization,PSO)算法应用于多目标作业车间调度问题(Flexibleiob shop scheduling problem,FJSP),提出一种新算法.算法在搜索初期利用粒子近邻的平均最优代替传统的单个最优引导搜索,后期用Gaussian动态概率搜索来提高算法的局部开挖能力.然后,引入Pareto优的概念,采用精英集来存放非劣解,提出一种新的适应度值分配方法.此外,在算法中还引入了一种自适应的变异算子来增强解的多样性.最后,用新算法对多组FJSP实例进行测试,并与其他几种方法进行比较,结果表明提出的算法具有较好的搜索性能,是求解多目标FJSP的一种可行方法.     

一种动态数据网格副本创建策略设计与仿真

数据网格提供了地理分布的大量共享数据资源,然而互联网的高访问延迟降低了数据访问的效率,创建副本是一个有效的方法,而在何处放置副本是一个具有挑战性的问题.从应用环境和用户访问特征出发,讨论了副本创建位置、粒度和时机,提出了一种基于副本共享组的副本创建模型,可以获得优化的副本创建位置,构造了一个副本创建代价函数,由系统的传输速率、拓扑结构和用户访问特征共同决定.并给出了确定副本创建位置的有效算法.分析和仿真实验表明,自适应副本管理方案具有动态性、适应性和可扩展性,能较好地适应数据网格的特性,可以有效降低访问延迟,提高数据访问效率.     

Research on the self-defence electronic jamming decision-making based on the discrete dynamic Bayesian network

The manner and conditions of running the decision-making system with self-defense electronic jamming are given.After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with self-defense electronic jamming,a decision-making model with self-defense electronic jamming based on the discrete dynamic Bayesian network is established.Then jamming decision inferences by the aid of the algorithm of discrete dynamic Bayesian network are carried on.The simulating result shows that this method is able to synthesize different targets which are not predominant.In this way,various features at the same time,as well as the same feature appearing at different time complement mutually;in addition,the accuracy and reliability of electronic jamming decision making are enhanced significantly.     

基于动态递归模糊神经网络盲均衡算法的研究

模糊系统和神经网络已广泛应用于系统的辨识和控制,但是传统的模糊神经网络是一种静态映射,不适用于动态系统的辨识;而由于无线通信信道的时变性和不确定性,决定了盲均衡器本身就是一个动态的均衡过程,所以研究利用动态递归模糊神经网络的盲均衡算法是可行的,而且也是必要的。仿真结果表明:由于动态模糊神经网络的均衡过程同时利用了系统的当前数据和历史数据,对动态系统的均衡,较传统神经网络在均衡的精度和稳定性方面具有更好的效果。