供应链视角下的增值税改革影响研究

构建了一个制造商和一个零售商所组成的两级供应链模型,研究增值税税率下调对供应链决策和社会福利的影响.结果表明,下调制造商、零售商增值税税率都会使产品零售价降低,提高零售商和制造商的利润.下调增值税税率给制造商带来的利润增量大于给零售商带来的利润增量.制造商税率下调导致批发价降低,零售商税率下调反而提高批发价.社会福利的变化趋势与潜在需求规模有关.当潜在需求规模较高时,社会福利总是随降税幅度的增大而增大,且税率降低后的社会福利大于税率降低前;当潜在需求规模中等时,社会福利随降税幅度的增大而减小,但税率降低后的社会福利仍大于税率降低前;当潜在需求规模较小时,社会福利随降税幅度的增大而减小,增值税税率下调损害了社会福利.     

不同补贴对象下闭环供应链信息共享价值研究

在一个制造商和一个零售商组成的二级闭环供应链中,为研究政府补贴下供应链需求信息共享对决策的影响及共享价值,针对两种补贴对象,构建并求解无信息共享和信息共享博弈模型,并进行仿真验证.研究表明:1)两种补贴对象下,制造商均能从信息共享中获益,零售商仅在绿色成本和回收成本较低时才会从信息共享中获益;绿色成本和回收成本稍高时,设计基于谈判势力的信息补偿机制能有效促进零售商共享信息.2)产品绿色度和回收率随预测需求量的提高而提高,批发价和零售价仅在回收成本较低时,才会随预测需求量的提高而提高.3)在仅补贴一方情况下,当补贴对象为低补贴一方时,两个主体所获的信息共享价值大;若对两者的补贴均较低,两个主体均希望补贴对象为零售商;若对两者的补贴均较高,零售商不愿共享需求信息.     

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.     

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.     

基于Chebyshev多项式的神经网络中长期负荷预测研究

高精度负荷预测在提高电力系统的安全性和经济性方面有着极其重要的意义,而现有的负荷预测方法因参数有限,难以完全反映其内在规律,因而导致预测结果不够准确.为此提出了一种基于Chebyshev多项式神经网络模型的预测方法.该方法使用递推最小二乘法训练神经网络权值系数,以获得高精度的参数估计,从而实现Chebyshev多项式神经网络模型对负荷量的最优拟合,再利用训练好的Chebyshev多项式神经网络模型实现中长期负荷预测.研究结果表明,该方法能较好模拟负荷变化规律,有效提高了负荷预测精度,在电力系统负荷预测中有较大的应用价值.     

广东省能源需求预测模型构建及实证分析

为了对广东省的能源需求进行准确的预测,首先分析了影响广东省能源需求的各种因素,构建了预测指标体系.在此基础上,针对能源系统非线性等复杂系统特征,结合粒子群算法和BP神经网络的优点,构建了改进的PSO-BP神经网络的预测模型,并通过主成分分析法对指标体系进行数据降维,以降低神经网络的规模和复杂程度.以广东省1985-2013年的能源需求数据进行模拟与仿真,并对2014-2018年的能源需求量进行预测,理论分析和实证研究表明,该方法能够很好的反映广东省能源需求的特征,预测结果较为准确合理.     

基于改进极根学习机的回转窑煅烧带温度预测方法

针对传统算法预测回转窑煅烧带温度存在精度低、速度慢的问题,提出了基于改进极限学习机(ELM)的回转窑煅烧带温度预测方法。对ELM输入权值矩阵定义了变换系数,采用黄金分割法在给定区间内搜寻变换系数的最佳值,改进了ELM网络参数的确定方式,弥补了随机确定输入权值并且不作调整的缺陷,在保证ELM训练速度的前提下提高预测精度、减小模型随机性。实验结果表明,改进的ELM预测精度高、训练速度快、模型性能优,可满足工况恶劣的回转窑的生产需要。     

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。     

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.