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.     

对气体输运分子数的讨论

说明担任气体输运任务的分子数是1/6nv和1/4nv的理论依据,并指出这两种分子数担任输运量得到的宏观规律相同的原因。     

基于数值模拟的注塑过程注射速率设计方法

给出一种注射速率的直接确定方法。数值模拟采用隐式控制体积法,利用等流率注射数值模拟获得熔体前沿的速度,该速度的倒数与充填百分比的曲线作为螺杆注射速率的相对变化曲线。经过二次注射过程的数值计算即可获得较均匀的熔体前沿速度。通过与现有文献中的结果比较,实例计算表明了本文方法的性能良好。     

爆速对纳米氧化铝尺度控制影响研究

将硝酸铝和黑索金按照不同的质量比均匀混合形成4种粉状的混合炸药,每一种炸药爆轰都得到了纳米氧化铝.对每次收集到的实验粉体分别进行了高分辨率透射电镜分析和X光衍射分析.分析结果表明4种混合炸药爆轰所得到的纳米氧化铝呈球形,颗粒尺寸分布比较均匀,尺寸范围为15～20 nm,晶型为γ型.另外由X光衍射数据利用Scherrer公式分别计算出每一种质量比的混合炸药爆轰所得到的纳米氧化铝的平均颗粒尺寸.利用BC-3型爆速仪测得4种混合炸药的实际爆速.研究发现爆速越高的混合炸药爆轰所得到的纳米氧化铝的颗粒就越细,同时绘出了爆速与颗粒尺寸的关系曲线.在一定的尺寸范围内,根据此曲线可以通过改变混合炸药的爆速来控制合成出的纳米氧化铝颗粒尺寸.     

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.     

Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

This paper uses the dynamic factor model framework, which accommodates a large cross‐section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components obtained from 282 quarterly macroeconomic time series in the period 1980:1 to 2006:4. The results, based on the root mean square errors of one to four quarters ahead out‐of‐sample forecasts over the period 2001:1 to 2006:4 indicate that, in the majority of the cases, the Dynamic Factor Model statistically outperforms the vector autoregressive models, using both the classical and the Bayesian treatments. We also consider spatial and non‐spatial specifications. Our results indicate that macroeconomic fundamentals in forecasting house price inflation are important. Copyright © 2010 John Wiley & Sons, Ltd.