铁路工程建设水土流失预测研究

随着铁路建设步伐的加快，铁路建设过程中引起的水土流失问题日益受到重视，以包兰线包头至惠农段电气化改造工程为研究对象，分析了沿线水土流失形式，确定了流失量，并对预测结果进行了总结。     

基于多尺度特征和支持向量机的股市趋势预测

应用支持向量机方法对股票市场趋势性变动进行预测是金融市场行为研究领域里一个重要的研究课题。为了提高股市趋势预测的准确率,现有文献中基本将研究重点集中在改善支持向量机参数上,而没有对输入数据的特征进行深入研究。股票市场时序数据是不同时间尺度因素非线性作用的结果,因此具有本质的多尺度特性。据此构建了股票市场多尺度时序特征趋势预测方法,该方法首先基于小波多分辨分析对股市时序数据进行多尺度分解,然后提取了股票市场数据的记忆性和趋势性特征,最后应用支持向量机对股票市场趋势进行预测,预测结果表明该方法提高了股市趋势预测的准确率。     

Myopic Analysis for Multi‐Echelon Inventory Systems with Batch Ordering and Nonstationary/Time‐Correlated Demands

We provide an exact myopic analysis for an N‐stage serial inventory system with batch ordering, linear ordering costs, and nonstationary demands under a finite planning horizon. We characterize the optimality conditions of the myopic nested batching newsvendor (NBN) policy and the myopic independent batching newsvendor (IBN) policy, which is a single‐stage approximation. We show that echelon reorder levels under the NBN policy are upper bounds of the counterparts under both the optimal policy and the IBN policy. In particular, we find that the IBN policy has bounded deviations from the optimal policy. We further extend our results to systems with martingale model of forecast evolution (MMFE) and advance demand information. Moreover, we provide a recursive computing procedure and optimality conditions for both heuristics which dramatically reduces computational complexity. We also find that the NBN problem under the MMFE faced by one stage has one more dimension for the forecast demand than the one faced by its downstream stage and that the NBN policy is optimal for systems with advance demand information and stationary problem data. Numerical studies demonstrate that the IBN policy outperforms on average the NBN policy over all tested instances when their optimality conditions are violated.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.     

运输供给的品质特性

在分析运输供需理论缺陷的基础上,将运输供给的品质特性重新界定为能被消费者感受到的、以运输过程为主体的、系统描述运输供给品质的指标体系。提出运输供给的品质特性由可达性、时效性、技术经济保障、经济性以及舒适性5个方面构成,并重新建立评价指标体系加以量化描述。鉴于运输供给具有鲜明的异质性,提出了区分不同类型运输需求(价格敏感型、品质敏感型和基本运输需求)、揭示运输供需关系和采用分类预测法预测运输需求的基本思路。     

时间序列的新息预报

根据实际问题，针对有限个数据ｗｋ，ｗｋ－１，…，ｗ１，给出了Ｗｋ＋ｌ的严格的线性最小方差预报和实现这种预报的适时递推公式和计算方法，并与平稳预报进行比较，得到两者有渐近相等的一步预报误差方差。     

Dynamic factor models

Summary Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an empirical application we demonstrate that these models turn out to be usefu in investigating macroeconomic problems.     

饱和增长趋势预测的自适应方法

讨论了商业、市场中大量存在的饱和增长过程的自适应预测问题,详细分析了自适应增长趋势预测尤其是Kalman滤波方法涉及的模型、模型变换、递推初值确定及趋势外椎等技术问题。     

Bayesian break-point forecasting in parallel time series,with application to university admissions

A regular supply of applicants to Queen's University in Kingston, Ontario is provided by 65 high schools. Each high school can be characterized by a series of grading standards which change from year to year. To aid admissions decisions, it is desirable to forecast the current year's grading standards for all 65 high schools using grading standards estimated from past year's data. We develop and apply a Bayesian break-point time-series model that generates forecasts which involve smoothing across time for each school and smoothing across schools. “Break point” refers to a point in time which divides the past into the “old past” and the “recent past” where the yearly observations in the recent past are exchangeable with the observations in the year to be forecast. We show that this model works fairly well when applied to 11 years of Queen's University data. The model can be applied to other data sets with the parallel time-series structure and short history, and can be extended in several ways to more complicated structures.     

基于GERT随机网络的废弃回收预测模型研究

在阐述回收处理业务流程的基础上,分析其不确定性;运用随机网络系统模型的相关理论构建GERT网络模型,探讨产品回收再制造零部件和可再生材料的预测模型。该模型既可以预测出废弃产品返回数量、回收处理过程中的再造零部件和可再生材料的比例和数量,又可以预测出它们的期望返回时间。最后,以打印机的回收再制造为例,对模型进行了实际应用。