高龄人口死亡率预测模型的比较与选择

高龄人口死亡率预测模型是人口预测、养老金成本和债务评估以及长寿风险度量与管理的基础。我国大陆地区高龄人口死亡数据量少、数据波动性大,如何选择适合我国高龄数据特点的死亡率预测模型,是重要的研究课题。本文在归纳总结死亡率预测模型研究进展的基础上,先采用数据较为充分的台湾地区高龄死亡数据,选用Lee-Carter、CBD、贝叶斯分层模型等八种死亡率模型,对模型的拟合效果、预测效果和稳健性做出比较。在此基础上,基于修正和平滑后的我国大陆人口死亡数据,采用CBD模型和贝叶斯分层模型建模和预测。结果显示:贝叶斯分层模型能捕捉我国大陆高龄死亡率数据的历史波动,预测区间能够涵盖全部死亡率的真实值,但预测区间过宽,生存曲线不收敛;相比之下,CBD模型对我国大陆地区高龄死亡率的拟合和预测较好,预测区间和生存曲线合理。在长寿风险度量中,建议采用CBD模型。     

基于线性二次型的永磁同步电机最优滑模控制

永磁同步电机的伺服控制系统是一个典型的非线性、强耦合、多输入多输出的系统,负载扰动和参数摄动都会使系统不稳定。针对这一问题,提出了一种基于线性二次型最优的滑模控制设计方法。将滑模控制与最优控制二者的优点相结合,设计了最优滑模控制律,并分别搭建基于传统滑模控制的永磁同步电机速度控制器和基于线性二次型最优的滑模速度控制器的仿真模型,在相同的条件下进行仿真,观察系统在两种控制器下的抗干扰能力。结果表明,不论系统受到突加负载信号还是突减负载信号的干扰,最优滑模控制器都具有很好的抗干扰能力,有效地增强了系统的鲁棒性。所提出的方法提高了永磁同步电机控制系统的动静态性能,对深入研究永磁同步电机控制系统具有一定的参考价值。     

On Long-term Forecasting of Social Security: A Robustness Analysis

In this paper we present a macro-economic demographic growth modelhaving a special focus on social security. It is designed to study the variability of responses of the system in presence of risks and uncertainties. Here we analyze the robustness of the model towards uncertainties in parameterspecifications, introduced by ARCH-M models with the incorporation ofintervention processes. The parameters varied are labor force participationrates (one of the key sources of uncertainty in the social security policydebate), and the parameters of the production function (the key source ofuncertainty in any long-run economic analysis). The sensitivity analysisfocuses on two variables: assets of the private pension system and thebalance of the public `Pay As You Go' pension system. Special attentionis given to convergence properties of the macro-economic model.     

Make a guess: a robust mechanism for King Solomon’s dilemma

We introduce endogenous fees for participating in second-price auction which we use for a two-stage mechanism to solve King Solomon’s dilemma. They are positive for all agents. They are nonetheless shown to maintain the agents’ incentives for truthful bidding and guarantee participation by the highest-value agent. This feature of the endogenous fees is powerful enough for the efficient outcome to uniquely result from one round elimination of weakly dominated strategies, followed by at most four rounds of iterative elimination of strictly dominated stage-strategies. We provide an extension to cases with n agents and k identical prizes. We thank Gary Charness, Harrison Cheng, Jeffrey Ely, Rod Garratt, Mamoru Kaneko, Xiao Luo, Albert Ma, and Steven Morris for helpful discussions. We also thank an anonymous referee for comments that have helped to improve the paper.     

基于复杂网络理论的企业营销网络鲁棒性分析

基于复杂网络理论,探讨企业营销网络拓扑结构及其演化机制。在此基础上,对企业营销网络鲁棒性进行了分析。企业营销网络的无标度性具有对随机攻击的鲁棒性,以及对于恶意破坏的脆弱性。为了提高企业营销网络对于恶意破坏的鲁棒性,通过改变网络的演化机制,消除其无标度特性,生成节点度指数分布的网络。     

县域银行业集中度与农村信用社稳健性关系的实证分析--基于区域性金融风险防范视角

实证分析结果表明。引入市场竞争对农村信用社稳健性的影响有显著差异。在经济较发达地区,竞争程度的提高对农村信用社稳健性水平有提升作用;在经济欠发达地区,引入竞争短期内不一定能够提高农村信用社稳健性水平。因此,经济较发达地区的县域金融市场应当积极引入市场竞争来促进农村信用社的稳健发展,而经济欠发达地区的农村信用社可以通过引入先进银行业机构的资本持股并引进其先进管理经验来增强其稳健性。     

一种基于时间轴小波变换的鲁棒性水印算法研究

针对视频水印常见的攻击和视频压缩攻击,文章提出了一种时间轴小波域的视频水印算法。该算法选取每个场景中连续的8帧视频嵌入水印,让8帧视频图像进行3重时间轴小波变换得到一个低频帧,通过自适应的方式将水印嵌入低频帧的DCT中低频系数中,从而有效地保证了水印的抗攻击性。实验结果表明,该视频水印系统在不可见的同时具有很强的鲁棒性和安全性。     

M步预测控制系统的理论分析

该文分析了M步预测器为基础的控制系统,并将其与Smith预测控制进行比较,可以得出M步预测控制不但对过程纯滞后特性具有明显的补偿效果,而且在系统的稳定性和鲁棒性上比Smith预测控制具有更好的性能。     

Machine learning algorithms for the creation of clinical healthcare enterprise systems

Clinical recommender systems are increasingly becoming popular for improving modern healthcare systems. Enterprise systems are persuasively used for creating effective nurse care plans to provide nurse training, clinical recommendations and clinical quality control. A novel design of a reliable clinical recommender system based on multiple classifier system (MCS) is implemented. A hybrid machine learning (ML) ensemble based on random subspace method and random forest is presented. The performance accuracy and robustness of proposed enterprise architecture are quantitatively estimated to be above 99% and 97%, respectively (above 95% confidence interval). The study then extends to experimental analysis of the clinical recommender system with respect to the noisy data environment. The ranking of items in nurse care plan is demonstrated using machine learning algorithms (MLAs) to overcome the drawback of the traditional association rule method. The promising experimental results are compared against the sate-of-the-art approaches to highlight the advancement in recommendation technology. The proposed recommender system is experimentally validated using five benchmark clinical data to reinforce the research findings.