多维时序因子灰色模式识别预测方法及其应用

本文引入浑沌理论中分形几何的思想并结合灰色系统理论关联分析及灰域预测原理,提出了多维时序因子灰色模式识别预测方法。并以珠江流域某河流的长期水文预测报为实例。     

基于Web的水库洪水预报调度系统的关键技术

在重大洪水预报、洪水调度决策过程中,如何有效地获取分布的遥远水库、水文站点的动态水雨情信息,让相关利益部门和防洪专家积极主动地参与决策过程中的模型分析计算和重要决策过程讨论,迅速形成正确结论,实现科学、高效的防洪调度决策,是Web环境下水库洪水预报调度系统需要解决的重大关键技术问题.文中简要介绍了Web应用环境下该系统的体系结构,重点阐述了支持多用户多方案的洪水预报模型、洪水调度模型抽象设计技术及数据库表设计方法,给出了多库联调交互方案生成设计的解决方案.上述思想已经体现在所开发的基于Web的洪水预报调度系统中,在实际应用中取得了很好的效果.     

应用灰色预测法预测柳江柳州市区河段氨氮含量的尝试

阐述灰色预测法原理及计算过程 ,并以该方法对柳江柳州市鸡喇断面氨氮含量进行预测 ,探讨提高预测精度的途径     

Nonlinear prediction of exchange rates with monetary fundamentals

This paper employs a neural network (NN) to study the nonlinear predictability of exchange rates for four currencies at the 1-, 6- and 12-month forecast horizons. We find that our neural network model with market fundamentals cannot beat the random walk (RW) in out-of-sample forecast accuracy, although it occasionally shows a limited market-timing ability. The neural network model without monetary fundamentals forecasts somewhat better for the British pound and the Canadian dollar. The model also exhibits some market-timing ability for the Deutsche mark at the 6- and 12-month horizons, and for the Canadian dollar at the 1-month horizon. In general, the model performs more poorly when it becomes more complex or when the forecast horizon lengthens. Our overall results are more on the negative side and suggest that neither nonlinearity nor market fundamentals appear to be very important in improving exchange rate forecast for the chosen horizons.     

An unobserved component model for multi-rate forecasting of telephone call demand: the design of a forecasting support system

An Unobserved Components (UC) Model based on an enhanced version of the Dynamic Harmonic Regression model, including new multi-rate and modulated cycle procedures, is used to develop a customised package for forecasting and signal extraction applied to hourly telephone call numbers made to Barclaycard plc. service centres, with a forecasting horizon of up to several weeks in advance. The paper outlines both the methodological and algorithmic aspects of the modelling, forecasting and signal extraction procedures, including the design and implementation of forecasting support software with a specially designed Graphical User Interface within the ^® computing environment. The forecasting performance is evaluated comprehensively in comparison with the well-known seasonal ARIMA approach.     

The relevance of business cycles in forecasting international tourist arrivals

Casual empiricism suggests that there may be a cyclical trend associated with international tourist arrivals in which variation around the linear trend can be formed by the interaction with other cyclical phenomena. This paper employs a simple model that incorporates a linear trend and sine function to capture these two characteristics in forecasting international tourist arrivals in Hong Kong. The model is extended to include a set of sine functions through the application of Fourier analysis to account for situations in which more than one phenomenon may be present in the time series. The forecasting accuracy of the model is compared with other forecasting approaches. Evaluation of the results using the mean absolute percentage error measure show that the forecasting performance of the extended model with a linear trend and two sine functions is superior in terms of accuracy when compared with other forecasting models.     

通信公网在小型水库洪水预警报系统中的应用

通过对福建省泉州市小型水库基本情况的调查，分析了小型水库洪水预警报系统通信组网的特点和难点，对比水情测报系统中采用不同通信方式组网的优点和缺点，优选出适合泉州市小型水库洪水预警报系统的通信组网方式，并很好地解决了利用公共通信网络，组建小型水库洪水预警报系统数据通信网络存在的问题和难点，为全面开展小型水库自动测报系统建设积累了实践经验。     

与GDP相关的生活需水量预测模型

在目前生活需水量多种预测方法中,往往回避将经济发展指标作为直接影响因素。本文用传统的预测方法,先对生活必需水量加以预测,然后单独考虑GDP对生活需水量的影响,建立了与GDP相关的生活需水量预测模型。用该模型对西安和北京两地的生活需水量进行预测,结果表明该模型进行生活需水量预测是可行的。     

难忘世纪之交的水文情报预报

世纪之交的1994～2005年是广西洪水灾害最为频繁的时期,也是最能体现水文情报预报价值的时期.为此,重点对1994,1996,1998,2001,2005年大洪水的水文情报预报进行了回顾,通过回顾让人看到了洪水预报存在的问题和所面临的压力.     

基于IOWA算子的组合预测模型在物流需求预测中的应用

根据2000~2009年宁波市物流需求的数据,采用灰色GM 1,,1,模型和一元线性回归模型进行组合优化,建立了基于诱导有序加权平均(IOWA)算子的物流需求量组合预测模型。结果表明基于IOWA算子的组合预测模型能有效提高预测精度,说明了该方法用于物流需求预测的可行性和有效性,并在此基础上对2010~2013年宁波市物流需求作出预测。