基于主客观信息综合判断的非线性拉开档次法

针对以最大程度的拉开被评价对象间差异的综合评价问题,通过分析线性拉开档次法存在的局限性,本文提出了一种基于主客观信息综合判断的非线性拉开档次法,旨在进一步丰富和完善拉开档次法的理论知识。首先对线性拉开档次法进行简单的介绍,并分析了线性拉开档次法的局限性;然后提出前提假设,给出非线性因子选取的原则以及确定指标序关系的方法,并给出排序后相邻指标重要程度比值的选取方法,根据评价原则利用规划模型求解各评价指标的权重系数,利用求得的指标权重采用非线性集结模型计算最终的评价结果;最后用一个算例验证了方法的有效性。     

基于"纵横向拉开档次法"的上市公司经营业绩评价

鉴于目前已具有较全面、完整、连续的有关上市公司各项指标的纵横向数据，为充分利用数据所蕴涵的信息，本文提出运用“纵横向拉开档次”的综合评价方法，其特点是使指标权重的确定能尽量将被评价对象在纵横向拉开档次。将该法运用于安徽地方板块的18家上市公司业绩评价，获得了各公司在1999～2001年间动态发展的分析结果。     

1995—2004年西部各省区经济运行状况的综合评价

选取合适的系统和评价指标,对所收集的数据进行无量纲化的处理,然后用“纵横向”拉开档次法对处理后的数据进行分析得到权重系数,建立综合评价模型并进行评价,最后用最大序差对评价结果进行分析总结.     

差异驱动型评价方法的稳定性及差异凸显能力比较

针对综合评价中方法种类繁多且无统一比较标准的问题,选取了四种突出被评价对象之间差异的评价方法,采用随机模拟的方式分别从评价方法的稳定性及对差异的凸显能力两个方面进行了比较分析。得出了四种方法稳定性由高到低分别为均方差法、最大离差法、熵值法、拉开档次法,且评价方法的稳定性越高,则其对差异的凸显能力反而越差的结论。该研究不仅验证了差异驱动型评价方法的相关特性,为评价者关于评价方法的选取提供了参考意见,而且随机模拟方法的应用,可为类似的多评价方法的比较问题提供技术参考。     

基于灰色关联度-云模型的群评价数据质量改进方法及应用研究

针对群评价中的数据质量问题, 从评价专家和评价值两个角度进行了异常数据处理, 提出了基于灰色关联度-云模型的群评价数据质量改进方法。基于改进的云距离模型测算被评价对象云和目标云之间的差距, 采用TOPSIS法进行评价排序。将数据质量改进方法和云距离模型用于区域物流竞争力群评价, 改进了群评价的数据质量, 提高了评价结果的稳定性和代表性。     

一种体现发展趋势的动态综合评价方法

针对动态综合评价中没有考虑被评价对象指标的发展趋势的问题,综合考虑评价指标的发展趋势、指标权重和时间权重的影响,构建了一种体现发展趋势的动态综合评价模型。定义了发展因子,用于表示被评价对象指标的发展趋势,在纵横向拉开档次法的基础上采用离差平方和最小化的方法确定指标权重,并建立了一种体现“厚今薄古”思想的时间函数来确定时间权重。最后,将该动态综合评价模型应用于中国西部地区宏观经济发展评价问题中。     

多层次系统的动态评价研究

针对多层次系统的动态评价问题,首先,应用极大不相关法筛选指标以去除重复的信息;其次,对指标进行一致化和无量纲化的预处理;再次,采用逐层纵横向拉开档次评价法确定评价对象在不同时刻的评价值;最后,应用时序几何平均算子来集结多个时间点的评价值,以得出最终的动态排序。这种方法没有丝毫主观色彩,适用于经济管理系统的动态评价问题。以评价电力企业的效益作为算例,说明了方法的应用价值。     

长三角地区城市经济综合实力的评价

为了对长江三角洲城市群的经济综合实力做合理的评价,提出用作为“纵横向”拉开档次法对城市综合经济实力进行评价,并通过16个城市的2000、2002和2003三年数据进行了实证分析,最后给出了这些城市综合经济实力的排序和分类.     

一种动态评价法在钢铁企业低碳竞争力评价中的应用

在企业竞争力评价过程中,经常会遇到周期性、偶然性等问题,为解决这类问题,笔者在综合前人所提出“拉开档次”这一研究思路的基础上对TOPSIS法进行了拓展,并采用该方法对我国部分钢铁企业低碳竞争力进行了评价。研究结果表明,相对于现行的静态评价法,该法具有动态性、灵活性、综合性等优点,可以从各种角度反映钢铁企业的低碳竞争力状况。实证研究既验证了本方法的实用性和有效性,又解决了评价周期内巨大变化影响评价结论的问题,为企业低碳竞争力动态评价的研究提出了一种新的拓展思路。     

基于F-DEA赋权耦合的军工企业装备维修能力评价模型

权重系数的确定是多指标综合评价中的核心问题.针对传统数据包络分析评价模型中对指标赋权方法研究的不足,以军工企业装备维修能力的评价为例,在构建装备维修能力评价指标的基础上,利用SPSS软件计算出各决策单元的因子得分,并依据可测函数的有关性质对非正得分进行转换,利用转换结果构建了数据包络分析的有关输入、输出矩阵,最终构建出基于因子分析（Factor Analysis, FA）与数据包络分析（Data Envelopment Analysis,DEA）的F-DEA赋权耦合模型.借助MATLAB 的运算结果,证明了该模型的可行性与有效性;并据此给出提高相应决策单元装备维修能力的关键因素及其改进方案.     

Volatility estimation for stochastic project value models

One of the key parameters in modeling capital budgeting decisions for investments with embedded options is the project volatility. Most often, however, there is no market or historical data available to provide an accurate estimate for this parameter. A common approach to estimating the project volatility in such instances is to use a Monte Carlo simulation where one or more sources of uncertainty are consolidated into a single stochastic process for the project cash flows, from which the volatility parameter can be determined. Nonetheless, the simulation estimation method originally suggested for this purpose systematically overstates the project volatility, which can result in incorrect option values and non-optimal investment decisions. Examples that illustrate this issue numerically have appeared in several recent papers, along with revised estimation methods that address this problem. In this article, we extend that work by showing analytically the source of the overestimation bias and the adjustment necessary to remove it. We then generalize this development for the cases of levered cash flows and non-constant volatility. In each case, we use an example problem to show how a revised estimation methodology can be applied.     

Regenerative structure of Markov chains simulated via common random numbers

A standard strategy in simulation, for comparing two stochastic systems, is to use a common sequence of random numbers to drive both systems. Since regenerative output analysis of the steady-state of a system requires that the process be regenerative, it is of interest to derive conditions under which the method of common random numbers yields a regenerative process. It is shown here that if the stochastic systems are positive recurrent Markov chains with countable state space, then the coupled system is necessarily regenerative; in fact, we allow couplings more general than those induced by common random numbers. An example is given which shows that the regenerative property can fail to hold in general state space, even if the individual systems are regenerative.     

Impulsive stabilization of stochastic functional differential equations

This paper investigates impulsive stabilization of stochastic delay differential equations. Both moment and almost sure exponential stability criteria are established using the Lyapunov–Razumikhin method. It is shown that an unstable stochastic delay system can be successfully stabilized by impulses. The results can be easily applied to stochastic systems with arbitrarily large delays. An example with its numerical simulation is presented to illustrate the main results.     

基于随机占优理论的网络传播与免疫特性研究

以传统SIS传播模型为例,建立网络传播稳定状态方程式,运用随机占优理论,比较不同网络结构的传播稳定状态,利用比较结果,进行网络免疫,在疾病爆发或信息传播过程中根据网络结构控制网络传播的方向和速度,对社会中涉及传播的问题提供一种新的解决思路.     

一类带乘性噪声随机分数阶微分方程Euler方法的弱收敛性与弱稳定性

本文主要在带加性噪声随机分数阶微分方程的基础上,研究了一类更为困难的带乘性噪声随机分数阶微分方程Euler方法的弱收敛性与弱稳定性,并得到了类似的结论.首先构造了数值求解带乘性噪声随机分数阶微分方程的Euler方法,然后证明当分数阶α满足0α1/2时,该方法是1/2-α阶弱收敛的和弱稳定的,文末数值试验的结果验证了理论结果的正确性.     

Stochastic asymptotical stability for stochastic impulsive differential equations and it is application to chaos synchronization

In this paper, the stochastic asymptotical stability of stochastic impulsive differential equations is studied, and a comparison theory about the stochastic asymptotical stability of trivial solution is established. From the comparison theory, we can find out whether the stochastic impulsive differential system is stochastic asymptotically stable by studying the stability of a deterministic comparison system. As an application of this theory, we study the problem of chaos synchronization in Chua circuit using impulsive method. Finally, numerical simulation is employed to verify the feasibility of our method.     

Modeling of degradation data via wiener stochastic process based on acceleration factor constant principle

This paper proposes a systematic method of modeling accelerated degradation data based on the acceleration factor constant principle. Wiener stochastic process is considered because it is the most extensively used for degradation modeling. For the Wiener stochastic processes with three different time functions, the parameter relationships, which should be satisfied under any two different stress levels, are deduced according to the acceleration factor constant principle. The deduced parameter relationships indicate the stress-related parameters, which are applied to establish accurate accelerated degradation models. In addition, the deduced parameter relationships provide a guidance to test the consistency of the degradation mechanisms under different stress levels. A hypothesis method based on Analysis of Variance is adopted to identify the accelerated stress levels with different degradation mechanism. The degradation data under these stress levels should not be used to assess the product's reliability. The methods of validating accelerated degradation models and reliability assessments are also proposed. The simulation results prove the feasibility and effectiveness of the proposed methods. From the numerical example, it is concluded that the accelerated degradation model established based on the acceleration factor constant principle is more credible and accurate.     

Multilevel hybrid split-step implicit tau-leap

In biochemically reactive systems with small copy numbers of one or more reactant molecules, the dynamics is dominated by stochastic effects. To approximate those systems, discrete state-space and stochastic simulation approaches have been shown to be more relevant than continuous state-space and deterministic ones. In systems characterized by having simultaneously fast and slow timescales, existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap (explicit-TL) method, can be very slow. Implicit approximations have been developed to improve numerical stability and provide efficient simulation algorithms for those systems. Here, we propose an efficient Multilevel Monte Carlo (MLMC) method in the spirit of the work by Anderson and Higham (SIAM Multiscal Model. Simul. 10(1), 2012). This method uses split-step implicit tau-leap (SSI-TL) at levels where the explicit-TL method is not applicable due to numerical stability issues. We present numerical examples that illustrate the performance of the proposed method.     

参激白噪声作用下蔡电路的脉冲控制

考察了参激白噪声和脉冲信号联合作用下蔡电路的渐近P阶矩稳定性问题,得到该随机脉冲系统的比较系统,从而可由该确定性比较系统的稳定性得到原随机脉冲系统的渐近P阶矩稳定性.并从理论上得到能使该随机脉冲系统渐近P阶矩稳定的参数取值范围,即在稳定区域内取值的参数组合能够用脉冲方法对该随机蔡电路实现混沌控制.最后用数值仿真验证了理论结果的正确性.