Optimal index shooting policy for layered missile defense system

In order to cope with the increasing threat of the ballistic missile(BM)in a shorter reaction time,the shooting policy of the layered defense system needs to be optimized.The main decisionmaking problem of shooting optimization is how to choose the next BM which needs to be shot according to the previous engagements and results,thus maximizing the expected return of BMs killed or minimizing the cost of BMs penetration.Motivated by this,this study aims to determine an optimal shooting policy for a two-layer missile defense(TLMD)system.This paper considers a scenario in which the TLMD system wishes to shoot at a collection of BMs one at a time,and to maximize the return obtained from BMs killed before the system demise.To provide a policy analysis tool,this paper develops a general model for shooting decision-making,the shooting engagements can be described as a discounted reward Markov decision process.The index shooting policy is a strategy that can effectively balance the shooting returns and the risk that the defense mission fails,and the goal is to maximize the return obtained from BMs killed before the system demise.The numerical results show that the index policy is better than a range of competitors,especially the mean returns and the mean killing BM number.     

基于偏好DEA模型的应急资源优化配置

从应急系统中应急资源的投入产出的整体相对效率考虑, 提出了新的资源优化配置的非参数DEA模型,对应急系统中应急资源总体利用情况进行了评价.在此基础上,考虑到决策者的偏好信息,构造了偏好的DEA资源配置决策模型.最后,通过对一个算例的具体分析,清楚地表明,在资源总量控制的情况下,利用本文提出的非参数偏好DEA模型对应急资源进行统筹安排和合理配置,可以大大提高应急系统的整体相对效率.     

Timing Prediction Error Volatility and Dynamic Asset Allocation

We solve a portfolio selection,problem in which,return predictability,risk predictability and transaction cost are incorporated.In the problem,both expected return,prediction error volatility,and transaction cost are time-varying.Our optimal strategy suggests trading partially toward a dynamic aim portfolio,which is a weighted average of expected future tangency portfolio and is highly influenced by the common fluctuation of prediction error volatility(CPE).When CPE is high,the investor would invest less and trade less frequently to avoid risk and transaction cost.Moreover,the investor trades more closely to the aim portfolio with a more persistent CPE signal.We also conduct an empirical analysis based on the commodities futures in Chinese market.The results reveal that by timing prediction error volatility,our strategy outperforms alternative strategies.     

An impact angle constraint integral sliding mode guidance law for maneuvering targets interception

An integral sliding mode guidance law(ISMGL)combined with the advantages of the integral sliding mode control(SMC)method is designed to address maneuvering target interception problems with impact angle constraints.The relative motion equation of the missile and the target considering the impact angle constraint is established in the longitudinal plane,and an integral sliding mode surface is constructed.The proposed guidance law resolves the existence of a steady-state error problem in the traditional SMC.Such a guidance law ensures that the missile hits the target with an ideal impact angle in finite time and the missile is kept highly robust throughout the interception process.By adopting the dynamic surface control method,the ISMGL is designed considering the impact angle constraints and the autopilot dynamic characteristics.According to the Lyapunov stability theorem,all states of the closed-loop system are finally proven to be uniformly bounded.Simulation results are compared with the general sliding mode guidance law and the trajectory shaping guidance law,and the findings verify the effectiveness and superiority of the ISMGL.     

Finite-Time and Fixed-Time Synchronization of Inertial Neural Networks with Mixed Delays

This paper considers the drive-response synchronization in finite-time and fixed-time of inertial neural networks with time-varying and distributed delays(mixed delays). First, by constructing a proper variable substitution, the original inertial neural networks can be rewritten as a first-order differential system. Second, by constructing Lyapunov functions and using differential inequalities,some new and effective criteria are obtained for ensuring the finite-time synchronization. Finally, three numerical examples are also given at the end of this paper to show the effectiveness of the results.     

Optimal Grading Policies in the Online Acquisition of Used Products

Although online reverse commerce(recommerce)is convenient and efficient,it is not without caveats.It limits recommerce firms’flexibility to offer personalized prices and may cause mismatched grading between the firms and sellers of used products.This study examines a recommerce firm’s decision on grading criteria and prices.We find that the firm’s optimal policy exhibits two distinctly different patterns depending on the trade value of the product.We demonstrate that sellers’overestimate and underestimate errors have qualitatively different effects on firm profitability,and the effects crucially rely on the type of optimal policy.These findings can apprise firms on how to preset sorting criteria and prices as well as reduce grading errors.     

Evolutionary game analysis of problem processing mechanism in new collaboration

This paper analyzes a problem processing mechanism in a new collaboration system between the main manufacturer and the supplier in the"main manufacturer-supplier"mode,which has been widely applied in the collaborative development management of the complex product.This paper adopts the collaboration theory,the evolutionary game theory and numerical simulation to analyze the decision-making mechanism where one upstream supplier and one downstream manufacturer must process an unpredicted problem without any advance contract in common.Results show that both players'decision-makings are in some correlation with the initial state,income impact coefficients,and dealing cost.It is worth noting that only the initial state influences the final decision,while income impact coefficients and dealing cost just influence the decision process.This paper shows reasonable and practical suggestions for the manufacturer and supplier in a new collaboration system for the first time and is dedicated to the managerial implications on reducing risks of processing problems.     

Metropolis-Hastings自适应算法及其应用

首先阐述Metropolis-Hastings算法实现的具体步骤,然后证明由此产生的Markov链满足细致平衡条件,从而以目标分布为不变分布.接下来给出几个计算实例,以说明提议函数及其方差的选取对采样结果的影响,并由此推出一种改进的自适应算法用以寻找合适的提议函数及其方差.最后,通过贝叶斯Logistic模型的例子说明M-H方法在贝叶斯分析中的应用,同时也检验M-H自适应算法的效果.     

地面站系统服务能力评估指标及其计算方法

针对地面站系统服务能力评估问题,研究了其评估指标及其计算方法.首先从卫星、地面站两个方面建立了地面站系统服务能力评估指标,并就各个指标以及指标的应用进行了分析.然后给出了两种指标计算方法:FCFS(First Come First Service)方法和启发式方法.最后通过实例仿真,表明该指标及方法能够较好的解决地面站系统服务能力评估问题中的是否增建新地面站、是否在某地面站中增加天线等重大决策问题.     

飞机朝后座椅的保护作用模型研究

为了进一步提高民航旅客运输的安全性和减少飞机事故的伤亡率,对飞机座椅朝后这一新概念,从安全防护的改善方面进行了系统分析和定量的描述,建立了冲撞缓冲效果的估算模型,进行了相关的简单试验,并分析了空难幸存案例,从中得出结论,如果把飞机座椅朝后安装,可以主动地、大幅度地提高事故中对人体的防护能力,减少伤害率.另外,通过比较发现,由此带来的改善,并不减少飞机原有的性能指标,也不增加成本和维护的复杂性.最后提出了分级布置飞机客舱座椅的建议,以便保留部分朝前的座椅供一些有偏好的旅客进行选择,使所有的座椅安全性都有所提高,起到了系统优化的作用.此模型为新一代面向用户的飞机设计,提供了一个系统安全分析的基础.     

线上易获得性、感知奢侈价值与奢侈品消费

基于产品稀缺性理论和奢侈品感知价值理论,构建了线上易获得性、奢侈品感知价值与购买意愿关系的理论模型。实证结果发现,线上易获得性对奢侈品感知价值中的炫耀价值和独特价值产生显著的负向影响,而对感知质量、享乐价值和自我价值没有显著影响。同时,研究结果还发现,消费者对奢侈品的感知价值会显著影响购买意愿,感知炫耀价值和独特价值在线上易获得性对奢侈品购买意愿的影响中起中介作用。     

系统思维方法与系统动力学在战略并购问题上的应用

本文根据系统思维方法,运用系统动力学（SD）模型对影响战略并购目标公司定价影响因素的影响机理进行了模拟分析。文中研究了主要影响因素,给出了问题的流图以及系统动力学仿真分析结果。     

关联规则挖掘中阈值协调器的设计与实现

针对动态的关联规则挖掘中阈值的合理设置问题,提出了一种阈值协调算法(TCA算法),以克服传统的主观经验设置阈值的局限。通过设计一个用于处理动态关联规则挖掘过程中矛盾规则的阈值协调器,以计算矛盾域为基础,动态调节阈值,求得规则的一个基本的阈值区间,达到客观设置阈值的目的。给出了该方法的具体步骤,通过实验证明了该算法的有效性。     

基于公司价值的可转债定价实证研究

可转换债券近年来发展迅速,其相应的定价研究也成为研究的重点.本文通过构建公司价值、股票价值及可转债价值三者之间的方程,提出了一种新的基于公司价值的可转债定价方法,并在实证研究的基础上,通过一个回归方程对可转债理论价值进行调整.最后,本文通过对12家可转债的理论价格和市场价格进行对比来检验该方法,认为该方法能获得接近于市场价格的可转债理论价格.     

信息不完全下联盟结构合作对策的比例Owen解

不完全信息下联盟结构合作对策(简称不完全信息对策)是指特征函数中部分联盟价值缺失的联盟结构合作对策.Owen值应用前提是可行联盟的特征函数完全已知,因此Owen值不适用于求解不完全信息对策.根据不完全信息对策中已知可行联盟的特征函数,定义了比例Owen值.比例Owen值按照"二步法"对合作收益值进行两个层次的分配:一是优先联盟之间,二是优先联盟内部.与Owen值不同的是,在优先联盟内部比例Owen值依据每个成员对所在优先联盟的贡献率切割优先联盟的所得收益.比例Owen值满足一定的个体理性,并且通过公理化证明可知:比例Owen值是满足有效性、线性、零元联盟性和比例性等性质的唯一解,具有一定优良的性质.最后,将比例Owen值应用到一带一路背景下供应链中局中人作为整体参与合作的问题中,作为不完全信息下多层次合作的一种分配方案.     

具有模糊联盟值n人对策的模糊Shapley值

研究了一类联盟收益值是模糊数的n人对策的模糊Shapley值。利用模糊数运算有关理论,通过建立公理化体系,对具有模糊联盟收益值n人对策的模糊Shapley值进行深入研究,证明了这类n人对策模糊Shapley值存在性与唯一性,并给出了此Shapley值的具体表达式。最后,将此模糊Shapley值作为收益分配方案应用到企业协作收益分配的实例中。     

关于上海股市极值收益渐近分布的实证研究

通过极值概率坐标图发现上海股市极值收益吴明显的曲线,说明极值收益具有非指数分布特征,呈属于极值Ⅱ型吸引场,随后依据极值理论利用参数及非参数方法澄清验证了广为人知却一直停留在感性认识的股票市场极值收益厚尾性。利用GEV模型实证拟合了上海股市极值收益分布形式,通过SHERMAN最优拟合优度检验得出上海股市极值收益分布服从Frechet分布。     

The generalized symmetric coalitional Banzhaf value for multichoice games with a coalition structure

With respect to multichoice games with a coalition structure,a coalitional value named the generalized symmetric coalitional Banzhaf value is defined,which is an extension of the Shapley value for multichoice games and the symmetric coalitional Banzhaf value for traditional games with a coalition structure.Two axiomatic systems are established：One is enlightened by the characterizations for the symmetric coalitional Banzhaf value,and the other is inspired by the characterizations for the Banzhaf value.     

基于相邻层间相似性的加速Splatting算法

利用体数据的相邻层数据间具有高度相似性、差异较小这一普遍特性设计了Splatting体绘制的加速算法。计算各层采样点对屏幕像素颜色值的贡献时，只计算与上一层同位置有数据差异的采样点对屏幕像素颜色值贡献的变化量，然后用这个变化量修改在该采样点影响范围内的屏幕像素颜色值。试验表明，新算法可以大大加速Splatting算法的速度。     

基于顾客价值的竞争战略开发方法

顾客价值是竞争优势的重要源泉。构建基于顾客价值的竞争战略是企业获取竞争优势的新途径。针对以往研究的不足，提出新的基于顾客价值构建竞争战略的方法，突出顾客期望价值的作用，拓展鉴别不同类型顾客价值要素的维度．并通过一个实例说明实施方法。