灰色动态模型及其在人口预测中的应用

一个国家人口的数量直接影响着其经济、社会的发展和资源的利用 ,中国是世界上人口的第一大国 ,人口问题一直是制约中国发展的第一因素 .本文应用灰色系统等维灰数递补动态预测模型 ,对中国未来5 0年的人口数量进行了动态预测 ,通过检验表明 ,该模型合理、方法简便可行、结果符合实际 ,为中国经济和社会发展的决策和研究提供了科学依据     

Multivariate dynamic modeling for Bayesian forecasting of business revenue

Forecasting enterprise-wide revenue is critical to many companies and presents several challenges and opportunities for significant business impact. This case study is based on model developments to address these challenges for forecasting in a large-scale retail company. Focused on multivariate revenue forecasting across collections of supermarkets and product categories, hierarchical dynamic models are natural: these are able to couple revenue streams in an integrated forecasting model, while allowing conditional decoupling to enable relevant and sensitive analysis together with scalable computation. Structured models exploit multi-scale modeling to cascade information on price and promotion activities as predictors relevant across categories and groups of stores. With a context-relevant focus on forecasting revenue 12 weeks ahead, the study highlights product categories that benefit from multi-scale information, defines insights into when, how, and why multivariate models improve forecast accuracy, and shows how cross-category dependencies can relate to promotion decisions in one category impacting others. Bayesian modeling developments underlying the case study are accessible in custom code for interested readers.     

关于三峡永久船闸高边坡快速施工地质超前预报的几个问题

文中就三峡永久船闸高边坡快速施工地质超前预报的几个问题进行了讨论。分别研究了三峡永久船闸高边坡施工地质超前预报的必要性，提出了超前预报技术思路，最后就高边坡岩体反分析及反馈设计问题、施工地质超前预报问题以及与监测相适应的超前处理及防护进行了分析。     

碳税政策下时变需求依赖库存与价格的供应链协调模型

研究由一个供应商和一个零售组成的二级供应链系统在碳税政策下的协调问题.对于市场需求率为时变函数且依赖于当前库存水平和销售价格的情形,建立分散式和集中式供应链决策模型.比较两种模型得出供应商和零售商合作能够提高供应链的整体利润但是也会产生更多的碳排放.分别利用批发价格契约和两部收费契约协调分散式决策模型得出供应链协调的条件.最后通过数值算例验证理论结果并分析碳税单价对供应链在两部收费契约下实现协调的影响.     

ITS示范工程对城市交通畅通性的贡献率研究

通过分析城市交通畅通性的影响因素及其与ITS(智能交通系统)的关系,挖掘ITS对城市交通畅通性的贡献率指标.搜集实证研究对象数据,采用灰色预测模型预测贡献率指标的数值,将ITS示范工程实施前后的数值进行对比,计算得到ITS示范工程对城市交通畅通性的贡献率.由贡献率结果判断ITS示范工程对城市交通畅通性的作用及ITS示范工程的实施效果如何,为未来ITS的发展提供相应的参考建议.     

The role of cloud tracking and passive microwave techniques in the short-term prediction of flood hazard on a regional scale

The role of remote sensing in enhancing the monitoring capabilities and the short-term prediction of the risk of flooding on a regional scale is addressed in this paper by means of the application of storm identification and cloud tracking techniques to a few case studies where cluster analysis based on infrared satellite imagery is used as the primary source of information. Polar satellite sensors, which provide passive microwave images, were also proposed in the literature for application in flood forecasting operational problems, though the accuracy of passive microwave techniques is only acceptable when rainfall estimates are integrated over quite large spatial and temporal scales. Climatological studies are well suited to make use of such data while the measure of instantaneous rainfall is still lacking of an adequate validation. A theoretical and numerical framework for the assessment of the reliability of passive microwave estimates of instantaneous rainfall within the typical resolution scales of polar satellite sensors is provided in the paper.

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Sommario Il ruolo delle tecniche di monitoraggio da sensori remoti nell'incrementare le potenzialità di previsione a breve termine del rischio di inondazione a scala regionale è analizzato nel presente lavoro attraverso l'applicazione di tecniche di identificazione ed inseguimento dei corpi nuvolosi ad alcuni casi di studio in cui le immagini satellitarie nella banda dell'infrarosso termico sono utilizzate come principale strumento di monitoraggio. In letteratura viene inoltre proposta l'utilizzazione, in applicazioni operative di previsione delle inondazioni, di sensori alle microonde passive montati su satelliti ad orbita polare: l'accuratezza di tali tecniche è tuttavia accettabile solo quando le stime di precipitazione vengono integrate su ampie scale spaziali e temporali. Mentre l'uso di tali tecniche per studi climatologici è di notevole utilità, la misura della precipitazione alle piccole scale spazio-temporali necessita ancora di un adeguato processo di validazione. Nel presente lavoro viene proposto un approccio teorico per la stima dell'affidabilità di tali stime di precipitazione alle scale tipiche della risoluzione spaziale del sensore.

     

A step-by-step guide to building two-population stochastic mortality models

Two-population stochastic mortality models play a crucial role in the securitization of longevity risk. In particular, they allow us to quantify the population basis risk when longevity hedges are built from broad-based mortality indexes. In this paper, we propose and illustrate a systematic process for constructing a two-population mortality model for a pair of populations. The process encompasses four steps, namely (1) determining the conditions for biological reasonableness, (2) identifying an appropriate base model specification, (3) choosing a suitable time-series process and correlation structure for projecting period and/or cohort effects into the future, and (4) model evaluation.For each of the seven single-population models from Cairns et al. (2009), we propose two-population generalizations. We derive criteria required to avoid long-term divergence problems and the likelihood functions for estimating the models. We also explain how the parameter estimates are found, and how the models are systematically simplified to optimize the fit based on the Bayes Information Criterion. Throughout the paper, the results and methodology are illustrated using real data from two pairs of populations.     

Hybrid evolutionary algorithms in a SVR traffic flow forecasting model

Accurate urban traffic flow forecasting is critical to intelligent transportation system developments and implementations, thus, it has been one of the most important issues in the research on road traffic congestion. Due to complex nonlinear data pattern of the urban traffic flow, there are many kinds of traffic flow forecasting techniques in literature, thus, it is difficult to make a general conclusion which forecasting technique is superior to others. Recently, the support vector regression model (SVR) has been widely used to solve nonlinear regression and time series problems. This investigation presents a SVR traffic flow forecasting model which employs the hybrid genetic algorithm-simulated annealing algorithm (GA-SA) to determine its suitable parameter combination. Additionally, a numerical example of traffic flow data from northern Taiwan is used to elucidate the forecasting performance of the proposed SVRGA-SA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal autoregressive integrated moving average (SARIMA), back-propagation neural network (BPNN), Holt-Winters (HW) and seasonal Holt-Winters (SHW) models. Therefore, the SVRGA-SA model is a promising alternative for forecasting traffic flow.     

Pre-operational forecasting of sea level height for the Río de la Plata

This paper presents the implementation and calibration of a pre-operational numerical model for the Río de la Plata river. This model is capable of predicting sea level variations in the Río de la Plata, and therefore constitutes a numerical tool of great value for the fluvial–maritime navigation and regional environmental management. A two-dimensional model (MOHID) with nested domains was used to simulate the hydrodynamics. This model was forced with a meso-scale atmospheric model (WRF) and a global tidal model (FES2004). The results obtained include astronomic and meteorological sea level variations in the Río de la Plata. Comparisons of modeled water levels with data have shown very good qualitative and quantitative agreement. The pre-operational test presented in this paper, a 4-day hydrodynamic forecast, was conducted in approximately 18 h.     

控制点优化磨光算法在长江径流量预测中的应用

盈亏修正磨光法所得到的逼近效果仍然很差,通过控制点的参数优化和目标函数的最小,提出一种控制点优化磨光算法,利用这个算法得到参数后代入模型,使预测的精度得到提高.通过实例,该算法简单易行,并通过相对误差进行了分析,控制点优化磨光算法所得到的预测值好于神经网络模型、PPAR和小波网络模型的预测值,这为研究磨光法提供了较好的分析方法.