Short‐term salmon price forecasting

This study establishes a benchmark for short‐term salmon price forecasting. The weekly spot price of Norwegian farmed Atlantic salmon is predicted 1–5 weeks ahead using data from 2007 to 2014. Sixteen alternative forecasting methods are considered, ranging from classical time series models to customized machine learning techniques to salmon futures prices. The best predictions are delivered by k‐nearest neighbors method for 1 week ahead; vector error correction model estimated using elastic net regularization for 2 and 3 weeks ahead; and futures prices for 4 and 5 weeks ahead. While the nominal gains in forecast accuracy over a naïve benchmark are small, the economic value of the forecasts is considerable. Using a simple trading strategy for timing the sales based on price forecasts could increase the net profit of a salmon farmer by around 7%.     

Bias‐corrected bootstrap prediction intervals for autoregressive model: new alternatives with applications to tourism forecasting

This paper proposes the use of the bias‐corrected bootstrap for interval forecasting of an autoregressive time series with an arbitrary number of deterministic components. We use the bias‐corrected bootstrap based on two alternative bias‐correction methods: the bootstrap and an analytic formula based on asymptotic expansion. We also propose a new stationarity‐correction method, based on stable spectral factorization, as an alternative to Kilian's method exclusively used in past studies. A Monte Carlo experiment is conducted to compare small‐sample properties of prediction intervals. The results show that the bias‐corrected bootstrap prediction intervals proposed in this paper exhibit desirable small‐sample properties. It is also found that the bootstrap bias‐corrected prediction intervals based on stable spectral factorization are tighter and more stable than those based on Kilian's stationarity‐correction. The proposed methods are applied to interval forecasting for the number of tourist arrivals in Hong Kong. Copyright © 2010 John Wiley & Sons, Ltd.     

Forecast robustness in macroeconometric models

This paper investigates potential invariance of mean forecast errors to structural breaks in the data generating process. From the general forecasting literature, such robustness is expected to be a rare occurrence. With the aid of a stylized macro model we are able to identify some economically relevant cases of robustness and to interpret them economically. We give an interpretation in terms of co‐breaking. The analytical results resound well with the forecasting record of a medium‐scale econometric model of the Norwegian economy.     

末端修正子母弹对面目标的射击效能评估

作为射击精度评估的常用指标,无论是圆概率偏差,还是命中概率都没有涉及面目标的功能结构的重要度,而命中重要程度不同的区域,其射击效能是不同的。针对末修子母弹打击面目标时射击效能的评价问题,在通过数值模拟法产生末修子母弹的落点散布,以及利用毁伤树分析方法对面目标进行功能区域划分的基础上,利用Monte-Carlo仿真方法计算了子母弹对各功能区域的命中概率Pi,并定义了基于区域结构及重要度的射击命中度和毁伤概率,从而综合评估了整体的射击效能。最后通过仿真算例说明了该方法的合理性,并利用均匀设计法定量分析了末修子母弹的性能参数对射击效能的影响。     

基于边缘点投影方差最小的车牌倾斜校正方法

在车牌识别系统中,为提高字符分割和识别的效果,需要对定位后的车牌图像进行倾斜校正.提出了一种基于边缘点投影方差最小的车牌倾斜校正方法.首先将旋转后车牌图像的垂直边缘向水平方向投影;然后导出边缘点投影方差最小时旋转角度的闭合表达式,由此一步确定车牌的倾斜角度;最后通过双线性插值方法校正车牌.给出了实验结果,并与车牌倾斜校正的Hough变换法、旋转投影法和主成分分析法进行了精确度、算法复杂度及运算时间的比较,结果表明所提出的方法精确度高、鲁棒性好、实时性强.通过进一步分析和推广,将车牌倾斜校正方法总结为两种不同类型的方法,并对它们进行了比较.     

Prediction in the two‐way random‐effect model with heteroskedasticity

In this paper we extend Taub (1979) approach for prediction in the context of the variance components model. The extension obtained is based on the two‐way random‐effect model with heteroskedasticity. Prediction functions are then obtained in three heteroskedasticity cases (heteroskedasticity on the individual term , heteroskedasticity on the composite term ?_it, and heteroskedasticity on the temporal term ). Copyright © 2008 John Wiley & Sons, Ltd.     

红外焦平面阵列非均匀校正算法研究

红外图像的非均匀性已经成为制约红外焦平面阵列成像质量的限制性因素。本文对红外非均匀性的定义和来源进行了深入的探讨,给出了几种非均匀校正算法及其实验结果,最后对各种校正算法的特点进行了归纳总结。     

A Method on Non-Linear Correction of Broadband LFMCW Signal Utilizing Its Relative Sweep Non-Linear Error

1. INTaODUCTIONLinear frequency modulation continuous wave (LFMCW) radar with broadband has a high range Precisinlland high resollltion because of its large time bandwidth product and has no blind range at the'sarne take.LFMCW radax has more extensive applications in many fields such as microwave ranging, crashworthy car, andmissile's terminal guidance because broadband LFMCW devices are being miniaturized and integrated with therapid developmellt of microwave and millimeter wave ill…     

PTN技术的发展与应用

从业务向AllIP转型对承载网提出了更高的需求,对MSTP和以太网技术的分析,提出了引入PTN技术的优势;PTN技术的探讨到对PTN设备的阐述,提出了以PTN和OTN联合组网的方式的发展前景。