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.     

Multi‐switching combination–combination synchronization of non‐identical fractional‐order chaotic systems

In this paper, multi‐switching combination–combination synchronization scheme has been investigated between a class of four non‐identical fractional‐order chaotic systems. The fractional‐order Lorenz and Chen's systems are taken as drive systems. The combination–combination of multi drive systems is then synchronized with the combination of fractional‐order Lü and Rössler chaotic systems. In multi‐switching combination–combination synchronization, the state variables of two drive systems synchronize with different state variables of two response systems simultaneously. Based on the stability of fractional‐order chaotic systems, the multi‐switching combination–combination synchronization of four fractional‐order non‐identical systems has been investigated. For the synchronization of four non‐identical fractional‐order chaotic systems, suitable controllers have been designed. Theoretical analysis and numerical results are presented to demonstrate the validity and feasibility of the applied method. Copyright © 2017 John Wiley & Sons, Ltd.     

基于可拓和组合赋权的矿井通风系统优化评价

矿井通风系统具有随机性、模糊性和不确定性等特征,一般单一的赋权评价法难以对其进行准确的优化评价.采用模糊层次分析法和熵权法的组合赋权法不仅可以提升对目标评价的准确性还能避免单一赋权的偶然性和局限性,结合可拓学的优度评价法,依据优度排序,得到最优方案.事实证明,基于组合赋权的可拓评价模型较其他评价方法更为客观,评价结果更加符合实际,可为解决类似优化方案问题提供一种新思路和方法.     

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.     

平面膜结构拓扑优化的有无复合体方法

将作者对桁架在应力约束下结构拓扑优化的有无复合体模型发展到平面膜结构在应力、位移约束下结构拓扑优化的建模与求解。同时提出了该模型的有效解法,获得了令人满意的数值结果。本文工作表明独立连续拓扑变量的提出对于结构拓扑优化的研究是有意义的。     

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.