远程教育课件点播平台业务模式及构建方案

远程教育产业现在正处于蓬勃发展的上升态势之中。在着眼未来的互联网领域,教育产业是一个十分令人看好的投资方向。本文主要简述远程教育课件点播平台业务模式及构建方案,并通过投资预算及业务预测,计算其收益及业务拓展。     

计算机辅助电力设备故障模式与影响分析方法

以近年来我国电力企业设备检修实践为基础,从状态检修管理体制、人员素质和技术检测手段等几个方面阐述了在向状态检修模式迈进的历程中所采取的措施、设想和面临的困难及解决的思路,并论述了计算机技术在其中的应用。     

RBF神经网络在物流系统中的应用

物流已经成为我们国民经济的动脉,但是影响其成本的因素过多且复杂,对其成本的研究目前较多的是采用简单的猜测式赋值,这样的方法具有较大的主观性,因此物流成本预测这个复杂的非线性问题已经成了物流界研究的重点问题。将社会物流系统看出了一个投入产出系统,将其物流成本——运输费用、保管费用和管理费用当作了投入,而社会的消费总额看成了产出,因此导出物流消费品总额和成本之间的映射关系模型;其次,提出用改进的自适应遗传算法对径向基函数神经网络进行了优化,得到了最佳的基函数中心和宽度值;最好用优化后的径向基函数神经网络应用于物流成本的预测,结果表明,模型具有好的稳定性和较高的精度,对扩大消费、拉动内需具有一定的参考意义。     

面向顾客选择的产品联合分析系统的研究与实现

运用联合分析原理建立数学模型,根据数学模型和项目情况进行系统分析设计,运用程序开发等相关技术实现在线产品分析系统,该系统提供给设计和销售人员进行产品调查和分析,从而提供产品各属性水平的效用值、重要性及产品潜在的市场占有率,以指导产品研发设计和产品进货选择.     

空间光通信中轨道短时预报

瞄准、捕获和跟踪(PAT)技术是星间光通信的关键技术之一,高精度卫星轨道短时预报能有效实现PAT.首先在EGM96地球引力场模型下建立了卫星状态动力方程和预报方程,然后改进基于数值算法的扩展卡尔曼滤波算法对卫星轨道短时预报,最后以champ卫星星载GPS实时定轨数据为卡尔曼滤波器观测数据进行仿真实验:预报卫星位置误差约亚米级,速度误差约0.05m/s;卫星位置和速度的均方差估计趋于稳定,在一定程度上能很好地克服离散误差和模型误差对轨道估计精度的影响.PAT瞄准精度约1.6 μrad.预报轨道精度能满足空间光通信PAT技术要求.     

建筑工程施工成本监测预警及协调控制

通过对施工成本影响因素的识别,建立了施工成本监测与预警信号模型,以及施工成本协调控制模型等。     

Comparison of forecasting methods with an application to predicting excess equity premium

This paper reviews various forecast methods including combination using theoretically optimal weights and those under model selection approaches. In addition, we suggest two modified simple averaging forecast combination methods—a mean corrected and a mean and scale corrected method. We conclude that due to the fact that real data is usually subject to structural breaks, rolling forecasting scheme has a better performance than fixed window and continuously updating scheme. In addition, methods that use less information appear to perform better than methods using all the sample information about the covariance structure of the available forecasts. The mean and scale corrected simple average approach yield smaller mean squared forecast error than the three widely used regression approaches suggested by Granger and Ramanathan [11].     

The behaviour of the multi-layer perceptron and the support vector regression learning methods in the prediction of NO and NO2 concentrations in Szeged, Hungary

The main aim of this paper is to predict NO and NO₂ concentrations 4 days in advance by comparing two artificial intelligence learning methods, namely, multi-layer perceptron and support vector machines, on two kinds of spatial embedding of the temporal time series. Hourly values of NO and NO₂ concentrations, as well as meteorological variables were recorded in a cross-road monitoring station with heavy traffic in Szeged, in order to build a model for predicting NO and NO₂ concentrations several hours in advance. The prediction of NO and NO₂ concentrations was performed partly on the basis of their past values, and partly on the basis of temperature, humidity and wind speed data. Since NO can be predicted more accurately, its values were considered primarily when forecasting NO₂. Time series prediction can be interpreted in a way that is suitable for artificial intelligence learning. Two effective learning methods, namely, multi-layer perceptron and support vector regression are used to provide efficient non-linear models for NO and NO₂ time series predictions. Multi-layer perceptron is widely used to predict these time series, but support vector regression has not yet been applied for predicting NO and NO₂ concentrations. Three commonly used linear algorithms were considered as references: 1-day persistence, average of several day persistence and linear regression. Based on the good results of the average of several day persistence, a prediction scheme was introduced, which forms weighted averages instead of simple ones. The optimization of these weights was performed with linear regression in linear case and with the learning methods mentioned in non-linear case. Concerning the NO predictions, the non-linear learning methods give significantly better predictions than the reference linear methods. In the case of NO₂, the improvement of the prediction is considerable, however, it is less notable than for NO.     

国外钢铁工业用耐火材料回顾与展望

首先从生产和使用两个侧面回顾了钢铁工业用耐火材料的概貌，进而简要地展示了其发展趋势。最后按钢铁工业的生产流程，分高炉、铁水预处理、炼钢炉、炉外精炼、钢包和连铸等七个方面，较详细地介绍了耐火材料在这些领域中的使用现状和前景。     

聚氯乙烯市场分析及预测

综述了PVC树脂国内外发展概况,国内产需平衡、进出口及“八五”发展情况。分析了国内PVC制品生产、使用及发展前景,对1992年PVC市场进行了预测,并提出了改进建议。