基于GIS空间分析的台风路径预测

建立了一种利用历史数据进行台风路径预测的模型。该模型应用关键点相似度法,利用地理信息系统(GIS)的空间分析功能,建立当前实测台风中心位置的缓冲区,从历史台风数据库中搜索路径相似的台风,确定各条路径的相似度;再依据相似度确定台风的相似权重,进行24~48 h的台风路径趋势的快速预测;根据每6 h的预测结果对预测结果进行修正。实例研究表明,24 h预测误差小于140 km,48 h预测误差小于240 km。     

To combine or not to combine? issues of combining forecasts

This paper addresses issues such as: Does it always pay to combine individual forecasts of a variable? Should one combine an unbiased forecast with one that is heavily biased? Should one use optimal weights as suggested by Bates and Granger over twenty years ago? A simple model which accounts for the main features of individual forecasts is put forward. Bayesian analysis of the model using noninformative and informative prior probability densities is provided which extends and generalizes results obtained by Winkler (1981) and compared with non-Bayesian methods of combining forecasts relying explicitly on a statistical model for the individual forecasts. It is shown that in some instances it is sensible to use a simple average of individual forecasts instead of using Bates and Granger type weights. Finally, model uncertainty is considered and the issue of combining different models for individual forecasts is addressed.     

A note on diagrams for turning-point diagnostics

A new diagram for discriminating a forecasting technique's history with respect to the two types of turning-point errors, missed turns and false signals is presented. This diagram extends Theil's original prediction-realization (P-R) presentation so that each of the four quadrants and the axes locates a distinct type of forecasting error or correct forecast, thus reducing much of the former ambiguity. This improvement is accomplished without the loss of any information.     

Forecast comparisons of four models of U.S. interest rates

In this paper we compare the out of sample forecasts from four alternative interest rate models based on expanding information sets. The random walk model is the most restrictive. The univariate time series model allows for a richer dynamic pattern and more conditioning information on own rates. The multivariate time series model permits a flexible dynamic pattern with own- and cross-series information. Finally, the forecasts from the MPS econometric model depend on the full model structure and information set. In theory, more information is preferred to less. In practice, complicated misspecified models can perform much worse than simple (also probably misspecified) models. For forecasts evaluated over the volatile 1970s the multivariate time series model forecasts are considerably better than those from simpler models which use less conditioning information, as well as forecasts from the MPS model which uses substantially more conditioning information but also imposes ‘structural’ economic restrictions.     

Linear regression forecasting in the presence of ar(1) disturbances

This paper is concerned with time-series forecasting based on the linear regression model in the presence of AR(1) disturbances. The standard approach is to estimate the AR(1) parameter, ρ, and then construct forecasts assuming the estimated value is the true value. We introduce a new approach which can be viewed as a weighted average of predictions assuming different values of ρ. The weights are proportional to the marginal likelihood of ρ. A Monte Carlo experiment was conducted to compare the new method with five more conventional predictors. Its results suggest that the new approach has a distinct edge over existing procedures.     

基于协整分析法的我国环保投资预测

通过协整检验和格兰杰因果检验法证实了环保投资与3个宏观经济变量人均GDP、财政支出、工业增加值之间具有长期均衡的协整关系和因果关系．利用建立的回归方程对于我国“十二五”期间的环保投资总量进行了预测．结果显示,我国“十二五”期间预计环保投资将达到3．98万亿元．最后,根据研究的结果,提出“十二五”期间环保投资相应的政策建议．     

预测未来的科学

“未来无法预测”的说法肯定是错误的。在科学基础上预测未来是常见的事,并不奇怪。典型例子如天气预报。而对地震的研究导致了地震学科的建立。客观世界遵循自然规律,但又是无规、随机、非线性和有突变的,因而预测未来既可能又很难成功。不能用因果性要求批评量子物理实验;可以用因果性对待经典物理实验,但不应死守“因先于果”的时序限制。因果律的精髓应是“在任何情况下果都不能影响因”。在Maxwell—d’Alembert方程求解过程中,完整的数学分析结果是有一个滞后解和一个超前解。过去的习惯作法是抛弃超前解而只留下滞后解,虽然从逻辑上的因果性出发而这样做并不合理,能被人们接受的理由只是“滞后解才与实验情况相符合”。现在已出现了众多的负波速实验,证明了超前渡存在,并且在实验中“果超前于因”。这些实验体现了“进入未来”的意蕴,或许可以看成是“时间机器”设想的某种体现。一般认为经过时空隧道可作时间旅行;也可利用量子力学现象,例如纠缠态和后选择。量子隐形传态传送的是量子态而非实体物质,从逻辑上讲量子后选择传态与时间旅行是一致的。因此旅行者实际上未动,而传送的是描写旅行者的全部信息。很明显,在量子理论中时间旅行是可能的。量子力学是未来学发展的动力。……然而未知事物大量存在,要承认未来充满了不确定性;对未来学的研究面临巨大困难,道路是漫长的。     

Economic and statistical measures of forecast accuracy

This paper argues in favour of a closer link between the decision and the forecast evaluation problems. Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming literature, and has continued to be used with meteorological forecasts, it is hardly mentioned in standard academic texts on economic forecasting. Some of the main issues involved are illustrated in the context of a two‐state, two‐action decision problem as well as in a more general setting. Relationships between statistical and economic methods of forecast evaluation are discussed and links between the Kuipers score used as a measure of forecast accuracy in the meteorology literature and the market timing tests used in finance are established. An empirical application to the problem of stock market predictability is also provided, and the conditions under which such predictability could be explained in the presence of transaction costs are discussed. Copyright © 2000 John Wiley & Sons, Ltd.     

Argo——成功的十年

由美、日等国科学家发起的国际Argo计划已经走过了10个年头,由3000多个自动剖面浮标组成的全球Argo实时海洋观测网也已于2007年10月末正式建成,成为全球海洋观测系统的重要支柱,迄今在全球海洋0—2000m深度范围内获取的温度、盐度和海流剖面资料总数已达56万余条,并正以每年10万条剖面以上的速度增加。随着Argo资料数量的快速增加和质量的不断提高。它们在海洋和大气等多个领域科学研究和业务活动中的应用也得到了长足发展,正有效地改变着人们对许多重大自然环境问题的认识,提高了人们对重大海洋和天气事件的预测预报能力。我国于2001年正式加入该计划,已经初步建立起我国的Argo大洋观测网,并在Argo资料的接收、处理和质量控制等方面积累了丰富的经验。但是,与其他国家相比,无论在重视程度和投入力度方面都还存在较大的差距。急需整合资源和力量,强化我国Argo大洋观测网的建设及其资料的应用研究,为应对全球气候变化做出更大的贡献。     

城市用水量预测的混沌理论研究

分析了混沌理论特征,利用城市用水量混沌特性,建立城市用水量短期预测模型,对城市用水量进行科学预测.利用历史数据信息,在相空间重构基础上对城市用水量时间序列进行分析,分析饱和嵌入维数、延迟时间和Lyapunov指数求解方法并对其进行计算,并以此为指导对城市用水量进行高精度预测.利用建立的模型对东北某市日用水量进行预测,结果表明基于混沌理论的城市用水量预测模型具有较高精度,对于受众多因素影响的城市用水量预测有良好的推广价值.城市用水量受众多因素影响,混沌理论为城市用水量预测提供了崭新思路.