北桥设计中的总线周期精确事务级建模

总线周期精确事务级建模能解决系统设计中的仿真精度和速度之间的矛盾。以北桥中的总线设计为背景,采用SystemC中接口方法调用的原理,实现了对Wishbone总线的周期精确事物级建模,并给出了具体的实现方法和测试方法,具有一定的通用性。     

Mur二阶吸收边界条件两种差分格式的比较

从理论上比较了时域有限差分法的Mur二阶吸收边界条件两种差分格式的计算精度、实现难度等,得出了直接格式计算精度较高但实现难度略大的结论.数值实验证实了上述结论.     

Hadamard变换光学编码探测中的定位精度研究

针对Hadamard光学成像的编码定位精度波动对编码成像结果的影响,研究了编码机制对定位偏差响应的表现,发现了阿达玛变换光学系统对定位精度波动的敏感性规律:像元强度改变量与定位偏差量成比例;一个编码周期内定位偏差的多次波动导致像元强度改变量按次累加;各次波动对像场强度改变量分布具有循环性.采用63阶码板实验以及数值模拟方法计算63阶、255阶和511阶S矩阵编码成像,结果表明定位精度的变化对编码成像质量有重要影响.给出了在编码成像中所应用的编码矩阵折叠形式与定位精度的相关关系,为编码成像系统的精度设计给出了理论基础.     

灵敏度分析在惯导平台误差参数辨识中的应用

为了解决传统的惯导平台测漂方案下,惯导平台上陀螺安装误差角的系统级辨识精度不高的问题,对平台漂移的非线性模型进行了灵敏度分析,找出了影响陀螺安装误差角辨识精度的主要因素,进而提出了转台相对地面存在角速率条件下的改进辨识方案.仿真结果表明,在改进的辨识方案下误差角的辨识精度获得了显著提高.     

虚拟装配环境体系结构的建模机制与分析设计

虚拟现实技术为产品开发带来了全新的人机界面和强大的功能,虚拟环境将虚拟现实技术与产品的设计、装配和分析紧密地结合在一起。但目前大多数面向产品开发的虚拟环境存在着通用性和可重用性等问题。本文给出了一个虚拟装配环境软件体系结构,该体系结构基于统一建模语言UML和离散事件系统形式化描述体系DEVS思想,采用面向对象、可重用技术对该系统进行了分析设计,实现了软件体系结构的可扩展性、可重用性和易维护性等。     

基于虚拟现实的产品公差分析

在阐述虚拟现实与虚拟装配技术内涵的基础上,重点论述了如何在虚拟现实环境下实现产品公差分析的方法以及对该技术应用前景的展望。     

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.     

Heterogeneous Forecast Adjustment

There is ample empirical evidence that expert‐adjusted model forecasts can be improved. One way to potential improvement concerns providing various forms of feedback to the sales forecasters. It is also often recognized that the experts (forecasters) might not constitute a homogeneous group. This paper provides a data‐based methodology to discern latent clusters of forecasters, and applies it to a fully new large database with data on expert‐adjusted forecasts, model forecasts and realizations. For the data at hand, two clusters can clearly be identified. Next, the consequences of having clusters are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Testing homogeneity of Japanese CPI forecasters

This paper investigates whether some forecasters consistently outperform others using Japanese CPI forecast data of 42 forecasters over the past 18 quarters. It finds that the accuracy rankings of 0, 1, 2, and 5‐month forecasts are significantly different from those that might be expected when all forecasters had equal forecasting ability. Moreover, their rankings of the relative forecast levels are also significantly different from a random one. Copyright © 2009 John Wiley & Sons, Ltd.     

Beating the VAR: Improving Swedish GDP Forecasts Using Error and Intercept Corrections

This paper examines the forecast accuracy of an unrestricted vector autoregressive (VAR) model for GDP, relative to a comparable vector error correction model (VECM) that recognizes that the data are characterized by co‐integration. In addition, an alternative forecast method, intercept correction, is considered for further comparison. Recursive out‐of‐sample forecasts are generated for both models and forecast techniques. The generated forecasts for each model are objectively evaluated by a selection of evaluation measures and equal accuracy tests. The result shows that the VECM consistently outperforms the VAR models. Further, intercept correction enhances the forecast accuracy when applied to the VECM, whereas there is no such indication when applied to the VAR model. For certain forecast horizons there is a significant difference in forecast ability between the intercept corrected VECM compared to the VAR model. Copyright © 2015 John Wiley & Sons, Ltd.