基于匹配序的合作对策联盟形成决策方法及其应用

合作对策中,联盟的形成过程是联盟一切活动的基础,直接影响着合作的稳定性与可持续发展。本文在分析局中人心理,情感,现实等因素对联盟形成所产生影响的基础上,首先定义了主观偏好标度值量化了心理、情感等因素,定义了收益分配函数将现实因素量化,构建了综合匹配函数作为局中人选择合作伙伴的一个序标准,通过定义匹配请求、交互匹配、直接交互匹配等概念,构建了基于匹配序的联盟形成决策模型,并证明了在特定情况下直接交互匹配的存在必然性。其次,给出了基于匹配序的联盟形成方法步骤,演化了大联盟的形成过程。最后通过具体实例验证了该决策方法的有效性与合理性。结果表明,该方法能有效的形成一系列可行且稳定的联盟结构,能快速演化联盟的形成过程,为有效解决联盟形成问题奠定了良好基础。     

The Theory of Finite Models without Equal Sign

In this paper, it is the first time ever to suggest that we study the model theory of all finite structures and to put the equal sign in the same situtation as the other relations. Using formulas of infinite lengths we obtain new theorems for the preservation of model extensions, submodels, model homomorphisms and inverse homomorphisms. These kinds of theorems were discussed in Chang and Keisler＇s Model Theory, systematically for general models, but Gurevich obtained some different theorems in this direction for finite models. In our paper the old theorems manage to survive in the finite model theory. There are some differences between into homomorphisms and onto homomorphisms in preservation theorems too. We also study reduced models and minimum models. The characterization sentence of a model is given, which derives a general result for any theory T to be equivalent to a set of existential-universal sentences. Some results about completeness and model completeness are also given.     

Sufficient and necessary conditions for stochastic near-optimal controls: A stochastic chemostat model with non-zero cost inhibiting

Near-optimal controls are as important as optimal controls for both theory and applications. Meanwhile, using inhibitor to control harmful microorganisms and ensure maximum growth of beneficial microorganisms (target microorganisms) is a very interesting topic in the chemostat. Thus, in this paper, we consider a stochastic chemostat model with non-zero cost inhibiting in finite time. The near-optimal control problem was constructed by minimizing the number of harmful microorganisms and minimizing the cost of inhibitor. We find that the Hamiltonian function is key to estimate objective function, and according to the adjoint equation, we obtain some error estimations of the near-optimality. Finally, we establish sufficient and necessary conditions for stochastic near-optimal controls of this model and numerical simulations and some conclusions are given.     

Hopf bifurcation and center stability for a predator–prey biological economic model with prey harvesting

In this paper, we investigate Hopf bifurcation and center stability of a predator–prey biological economic model. By employing the local parameterization method, Hopf bifurcation theory and the formal series method, we obtain some testable results on these issues. The economic profit is chosen as a positive bifurcation parameter here. It shows that a phenomenon of Hopf bifurcation occurs as the economic profit increases beyond a certain threshold. Besides, we also find that the center of the biological economic model is always unstable. Finally, some numerical simulations are given to illustrate the effectiveness of our results.     

Hydrodynamics for a system of harmonic oscillators perturbed by a conservative noise

We consider a heat conduction model for solids. Nearest neighbour atoms interact as coupled oscillators exchanging velocities in such a way that the total energy is conserved. The system is considered under periodic boundary conditions. We will show that the system has a hydrodynamic limit given by the solution of the heat equation and we discuss some aspects of the model.     

A neural network to solve quadratic programming problems with fuzzy parameters

In this paper, a representation of a recurrent neural network to solve quadratic programming problems with fuzzy parameters (FQP) is given. The motivation of the paper is to design a new effective one-layer structure neural network model for solving the FQP. As far as we know, there is not a study for the neural network on the FQP. Here, we change the FQP to a bi-objective problem. Furthermore, the bi-objective problem is reduced to a weighting problem and then the Lagrangian dual is constructed. In addition, we consider a neural network model to solve the FQP. Finally, some illustrative examples are given to show the effectiveness of our proposed approach.     

数学机械化中的AC=BD模式

介绍了AC=BD模式及其在用机械化方法求解方程和证明定理中的应用.首先证明对可单值化算子D,如果CKerD C KerA,则存在算子B使AC=BD.利用带余除法对于给定的算子A给出了求其(C-D对的算法,使得AC=BD.并将其应用到求解算子方程,可以将一些较为复杂的方程化为简单方程求解.其次,利用对偶算子给出了将非线性非交换算子方程组化为单个方程求解的算法.最后,利用解方程的方法给出了机械化产生并证明定理的模式,并且给出了一些实例.     

具有学习效应的超前有奖延误受罚的排序问题(英文)

本文考虑具有学习效应和共同交货期的单机排序问题.目标函数是加权超前有奖延误受罚总和.我们的目标是寻找一个最优序使得目标函数的值最小.由于该问题是NP-hard的,我们给出一些特殊情况下多项式时间可解的特例.同时在快速估计下界的基础上给出了分支定界算法来求一般情况下的最有排序.     

具有学习效应的超前有奖延误受罚的排序问题(英)

本文考虑具有学习效应和共同交货期的单机排序问题.目标函数是加权超前有奖延误受罚总和.我们的目标是寻找一个最优序使得目标函数的值最小.由于该问题是NP-hard的,我们给出一些特殊情况下多项式时间可解的特例.同时在快速估计下界的基础上给出了分支定界算法来求一般情况下的最有排序.     

Asymptotic behavior of a stochastic virus dynamics model with intracellular delay and humoral immunity

In this paper, we formulate a stochastic virus dynamics model with intracellular delay and humoral immunity. By constructing some suitable Lyapunov functions, we show that the solution of stochastic model is going around each of the steady states of the corresponding deterministic model under some conditions. Then, numerical simulations are given to support the theoretical results. Finally, we propose several more effective way to control the spread of the virus by analyzing the sensitivity of the threshold of spread.     

鞅差序列加权和的中心极限定理

对一类鞅差序列,我们获得了其加权和中心极限定理,并给出了在非线性回归模型及线性模型中的应用。     

Effectiveness in RPL, with applications to continuous logic

In this paper, we introduce a foundation for computable model theory of rational Pavelka logic (an extension of ?ukasiewicz logic) and continuous logic, and prove effective versions of some related theorems in model theory. We show how to reduce continuous logic to rational Pavelka logic. We also define notions of computability and decidability of a model for logics with computable, but uncountable, set of truth values; we show that provability degree of a formula with respect to a linear theory is computable, and use this to carry out an effective Henkin construction. Therefore, for any effectively given consistent linear theory in continuous logic, we effectively produce its decidable model. This is the best possible, since we show that the computable model theory of continuous logic is an extension of computable model theory of classical logic. We conclude with noting that the unique separable model of a separably categorical and computably axiomatizable theory (such as that of a probability space or an L^p Banach lattice) is decidable.     

The Generalized Cross Entropy Method, with Applications to Probability Density Estimation

Nonparametric density estimation aims to determine the sparsest model that explains a given set of empirical data and which uses as few assumptions as possible. Many of the currently existing methods do not provide a sparse solution to the problem and rely on asymptotic approximations. In this paper we describe a framework for density estimation which uses information-theoretic measures of model complexity with the aim of constructing a sparse density estimator that does not rely on large sample approximations. The effectiveness of the approach is demonstrated through an application to some well-known density estimation test cases.     

An upper bound of the number of tests in pooling designs for the error-tolerant complex model

Recently pooling designs have been used in screening experiments in molecular biology. In some applications, the property to be screened is defined on subsets of items, instead of on individual items. Such a model is usually referred to as the complex model. In this paper we give an upper bound of the number of tests required in a pooling design for the complex model (with given design parameters) where experimental errors are allowed.     

Dynamical analysis and control strategies on malware propagation model

A variable infection rate is more realistic to forecast dynamical behaviors of malware (malicious software) propagation. In this paper, we propose a time-delayed SIRS model by introducing temporal immunity and the variable infection rate. The basic reproductive number R₀ which determines whether malware dies out is obtained. Furthermore, using time delay as a bifurcation parameter, some necessary and sufficient conditions ensuring Hopf bifurcation to occur for this model are derived. Finally, numerical simulations verify the correctness of theoretical results. Most important of all, we investigate the effect of the variable infection rate on the scale of malware prevalence and compare our model with stationary analytical model by simulation. According to simulating results, some strategies that control malware rampant are given, which may be incorporated into cost-effective antivirus policies for organizations to work quite well in practice.     

Model-free feature screening for ultrahigh-dimensional data conditional on some variables

In this paper, the conditional distance correlation (CDC) is used as a measure of correlation to develop a conditional feature screening procedure given some significant variables for ultrahigh-dimensional data. The proposed procedure is model free and is called conditional distance correlation-sure independence screening (CDC-SIS for short). That is, we do not specify any model structure between the response and the predictors, which is appealing in some practical problems of ultrahigh-dimensional data analysis. The sure screening property of the CDC-SIS is proved and a simulation study was conducted to evaluate the finite sample performances. Real data analysis is used to illustrate the proposed method. The results indicate that CDC-SIS performs well.     

多次分组会议安排的最佳混合方案

本文在仔细分析问题条件和要求的基础上,运用了运筹学、图论、矩阵理论和置换等方面的知识和技巧,建立了一个布尔规划模型。     

The age of the arrival process in the G/M/1 and M/G/1 queues

This paper shows that in the G/M/1 queueing model, conditioning on a busy server, the age of the inter-arrival time and the number of customers in the queue are independent. The same is the case when the age is replaced by the residual inter-arrival time or by its total value. Explicit expressions for the conditional density functions, as well as some stochastic orders, in all three cases are given. Moreover, we show that this independence property, which we prove by elementary arguments, also leads to an alternative proof for the fact that given a busy server, the number of customers in the queue follows a geometric distribution. We conclude with a derivation for the Laplace Stieltjes Transform (LST) of the age of the inter-arrival time in the M/G/1 queue.     

Properties of some statistics for AR-ARCH model with application to technical analysis

In this paper, we investigate some popular technical analysis indexes for AR-ARCH model as real stock market. Under the given conditions, we show that the corresponding statistics are asymptotically stationary and the law of large numbers hold for frequencies of the stock prices falling out normal scope of these technical analysis indexes under AR-ARCH, and give the rate of convergence in the case of nonstationary initial values, which give a mathematical rationale for these methods of technical analysis in supervising the security trends.     

一类基于OWA算子的组合预测模型及其性质

本文引进近年来提出的有序加权平均（OWA）算子，建立新的组合预测模型。首先指出最大绝对误差最小化的组合预测模型是其特例，并给出其线性规划的求解方法；然后对该模型提出非劣性组合预测、预测方法优超，冗余度等新概念；最后探讨了非劣性组合预测以及冗余预测方法的存在性，并给出冗余信息的判定定理。