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.     

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.

     

灰色Verhulst神经网络组合预测区域空域流量

能够对区域空域的流量做出准确的预测,可以为空中交通管理部门协调航班运行,减缓空域内航路的拥堵提供重要依据.运用灰色Verhulst模型与神经网络的组合模型对区域航班流量进行预测,并结合华东地区飞行流量的数据样本训练并测试模型.结果显示,由组合模型得出的流量预测值与实际值较吻合,说明组合模型比单种预测方法能够更为准确地对区域空域流量做出预测.     

博弈论在通信对抗态势预测中的应用

本文首先提出了基于博弈论预测电磁态势演变的基本构想,设置了通信对抗的场景并构建了相应的数学模型.其次,分析了通信对抗电磁态势生成流程,最后结合一定的作战背景进行了仿真实验,基于双方博弈的原则预测了通信对抗态势的演变.仿真结果与理论分析相符,该研究成果已在多个作战仿真系统中得到了成功应用.