具有最高代数次数的2n元n维Bent函数的构造

本文给出了代数次数达到最高的一类布尔置换的代数标准形 ;并用m序列的状态转移矩阵和所得置换 ,构造了一类代数次数达到最高的 2n元n维Bent函数 ,用这类函数所构造的S盒具有较高的安全强度 .     

带平行约束的多处理机调度问题的模拟平衡方法

对带平行约束的多处理机调度问题给出一种随机状态转移方式，并通过大量的计算结果表明，这种状态转移方式具有根强的倾向性和遍历性，进而对通常的问题仅需经过很少的状态转移次数就可以获得精度很高的近似解。     

标准三点转移函数

一般的三点转移函数(TTF),不便用转移矩阵来表示.对于标准三点转移函数(STTF),引入了3类联络矩阵,研究了它们的一般特性和基本关系,给出了常值型标准三点转移函数的生成方法和状态对称型标准三点转移函数的一般表达形式.     

基于灰色马尔可夫模型的节能设备故障预测研究

精准预测节能设备故障可以有效节约节能服务公司运营成本,直接关系到节能服务公司的节能项目管理.根据灰色系统理论,将灰色均值GM(1,1)模型与马尔可夫模型融合,通过灰色马尔可夫模型预测节能设备的故障状况.具体而言,首先通过灰色均值GM(1,1)模型预测节能设备的未来故障情况,然后通过马尔可夫状态转移矩阵确定未来节能设备故障的可能状态,最后基于预测值与实际值的比值关系修正预测结果,以实现对节能设备故障次数的精准预测.结果表明灰色马尔可夫模型提高了预测精度,为精准预测节能设备故障提供了一种新思路.     

对经典隐马尔可夫模型学习算法的改进

改进经典隐马尔可夫模型(HMM)的状态转移和输出观测值的假设条件,并在经典隐马尔可夫模型的基础上导出新模型的学习算法.新算法避免了经典隐马尔可夫模型中状态转移概率和输出观测值概率计算时只考虑当前状态而不考虑历史的简单做法.     

一种估算马尔柯夫状态转移概率矩阵的新方法

在现有文献研究的基础上,对马尔柯夫状态转移概率矩阵估算方法又作了进一步研究,根据马尔柯夫状态转移概率矩阵的性质和特点,提出了一种新的估算方法.方法首先构造了一个以相对误差绝对值之和最小为目标,以某一状态转移到其他状态的概率之和等于1以及状态转移概率不小于零为约束条件的优化模型.在此基础上,通过变量替换,将该模型转化为线性规划模型.由于线性规划模型不仅能够求得解析解,而且有现成的求解软件,因此不但便于问题求解,而且更加方便、可靠.最后进行了示例计算,验证了给出的马尔柯夫状态转移概率矩阵优化算法的可行性和正确性.     

基于状态转移模型的条件期望与方差——从2状态到N状态的推广

基于状态转移模型计算的条件期望与方差,可以应用到金融领域,计算和度量市场在不同状态下的收益与风险.Nielson基于2状态转移模型,计算了2状态下股市的收益率的条件期望与方差.然而,实际研究中,常需要用到3状态、甚至多状态的状态转移模型.因此,基于Nielson的研究,从2状态推广到了$N$状态.基于$N$状态转移模型计算了条件期望、条件方差及无条件期望、无条件方差,该结果更具普遍性且形式更为简洁.最后,采用计算期望与方差的方法,分析中国股市收益率与波动率.实证结果表明,中国股市除存在牛市、熊市外,还存在政策市,且其具有`` 低风险,高收益"的特点.利用$N$状态转移模型计算的期望与方差可以更合理地度量金融市场在不同情况下的收益与风险.     

不同元件构成系统中元件维修率分布确定

将Markov链引入SFT理论中,计算可表示环境因素影响的元件维修率分布.研究针对不同元件构成的串联、并联和混联系统中元件的维修率分布计算方法.给出了串联和并联系统中元件维修率推导过程.对状态转移概率的计算不使用Markov状态转移矩阵求解,而是根据Markov状态转移图中的状态关系求解.使用SFT中的元件故障概率分布代替Markov链中的失效率,可得到元件维修率分布.以混联系统作为实例进行分析,使用状态关系求解各状态转移概率关系,得到了3个元件在使用时间t和使用温度c影响下的维修率分布,及正常状态转移概率范围.     

基于马尔科夫状态转移模型的天气衍生品定价

引入马尔科夫状态转移(MRS)模型拟合长沙市每日平均气温变化,利用最大期望算法估计马尔科夫状态转移模型参数,通过误差分析得到了最佳MRS模型.基于最佳的MRS模型,采用无套利定价原理定价气温衍生品,并利用蒙特卡罗方法得到了取暖指数(HDD)欧式看涨期权的数值解.实证结果表明,五状态的MRS模型对长沙市每日平均气温变化的拟合效果明显优于其他的MRS模型,它使得气温衍生品定价结果相比以前的方法更为精确.     

线性系统最优输出转移问题的反馈解

在适当的条件下讨论如何最佳地施加控制将系统的输出转移至目标点,用来度量控制优劣的指标综合反映了转移时间,转移过程所消耗的输入能量与系统自身运动过程所具有的能量的多少,给出了使此指标达到最小的(状态)反馈控制.     

马氏双链函数的强大数定律及其应用

本文研究了马氏随机环境中马氏双链函数的强大数定律.利用将双链函数进行分段研究的方法,获得了马氏环境中马氏双链函数强大数定律成立的一个充分条件.运用该定律,推导出马氏双链从一个状态到另一个状态转移概率的极限性质,进而推广了马氏双链的极限性质.     

Teaching practices aimed at promoting meta-level learning: The case of complex numbers

In this paper we seek to promote a conceptualization of “teaching toward meta-level learning” based on theoretical and empirical aspects. We adopt the commognitive distinction between object- and meta-level learning, and relate to meta-level learning as involving changes in the metarules that govern the discourse. Specifically, we refer to changes in the discourse on numbers emerging in the shift in discourse from real to complex numbers. We applied implications from the commognitive theory about meta-level learning to the planning and teaching of a lesson about complex numbers. Then, we analyzed the lesson to identify teaching practices that could promote meta-level learning. We found that these teaching practices can be clustered into three theory driven sub-sets: those referring to students’ current discourse on numbers, those referring to their new discourse and those referring to the transition between the two.     

Editorial

Linear programming problems with fuzzy parameters are formulated by fuzzy functions. The ambiguity considered here is not randomness, but fuzziness which is associated with the lack of a sharp transition from membership to nonmembership. Parameters on constraint and objective functions are given by fuzzy numbers. In this paper, our object is the formulation of a fuzzy linear programming problem to obtain a reasonable solution under consideration of the ambiguity of parameters. This fuzzy linear programming problem with fuzzy numbers can be regarded as a model of decision problems where human estimation is influential.     

p-Adic elliptic quadratic forms,parabolic-type pseudodifferential equations with variable coefficients and Markov processes

In this article we study the Cauchy problem for a new class of parabolic-type pseudodifferential equations with variable coefficients for which the fundamental solutions are transition density functions of Markov processes in the four dimensional vector space over the field of p-adic numbers.     

A generalization of carries processes and Eulerian numbers

We study a generalization of Holteʼs amazing matrix, the transition probability matrix of the Markov chains of the ‘carries’ in a non-standard numeration system. The stationary distributions are explicitly described by the numbers which can be regarded as a generalization of the Eulerian numbers and the MacMahon numbers. We also show that similar properties hold even for the numeration systems with the negative bases.     

Search heuristics and the influence of non-perfect randomness: examining Genetic Algorithms and Simulated Annealing

Simulated Annealing and Genetic Algorithms are important methods to solve discrete optimization problems and are often used to find approximate solutions for diverse NP-complete problems. They depend on randomness to change their current configuration and transition to a new state. In Simulated Annealing, the random choice influences the construction of the new state as well as the acceptance of that new state. In Genetic Algorithms, selection, mutation and crossover depend on random choices. We experimentally investigate the robustness of the two generic search heuristics when using pseudorandom numbers of limited quality. To this end, we conducted experiments with linear congruential generators of various period lengths, a Mersenne Twister with artificially reduced period lengths as well as quasi-random numbers as the source of randomness. Both heuristics were used to solve several instances of the Traveling Salesman Problem in order to compare optimization results. Our experiments show that both Simulated Annealing and the Genetic Algorithm produce inferior solutions when using random numbers with small period lengths or quasi-random numbers of inappropriate dimension. The influence on Simulated Annealing, however, is more severe than on Genetic Algorithms. Interestingly, we found that when using diverse quasi-random sequences, the Genetic Algorithm outperforms its own results using quantum random numbers.     

Control of the transition between regular and mach reflection of shock waves

A control problem was considered that makes it possible to switch the flow between stationary Mach and regular reflection of shock waves within the dual solution domain. The sensitivity of the flow was computed by solving adjoint equations. A control disturbance was sought by applying gradient optimization methods. According to the computational results, the transition from regular to Mach reflection can be executed by raising the temperature. The transition from Mach to regular reflection can be achieved by lowering the temperature at moderate Mach numbers and is impossible at large numbers. The reliability of the numerical results was confirmed by verifying them with the help of a posteriori analysis.     

Markov-type fuzzy decision processes with a discounted reward on a closed interval

We formulate a new multi-stage decision process with Markov-type fuzzy transition, which is termed Markov-type fuzzy decision process. In the general framework of the decision process, both of state and action are assumed to be fuzzy itself. The transition of states is defined using the fuzzy relation with Markov property and the discounted total reward is described as a fuzzy number on a closed bounded interval. To discuss the optimization problem, a partial order of convex fuzzy numbers is introduced. In this paper the discounted total reward associated with an admissible stationary policy is characterized by a unique fixed point of the contractive mapping. Moreover, the optimality equation for the fuzzy decision model is derived under some continuity conditions. Also, an illustrated example is given to explain the theoretical results and the computation in the paper.     

超音速后掠椭圆柱横流定常涡的不稳定特性及转捩预测

实验发现,一定条件下超声速后掠圆柱的前半圆上可能发生定常涡引起的转捩.为了模拟高空超音速飞行器后掠翼前缘,以无限展向长度后掠椭圆柱为模型,基于eN方法,根据积分的N值,分析了迎风轴长度、Reynolds(雷诺)数、后掠角和Mach(马赫)数等参数的变化对超音速后掠椭圆柱横流定常涡不稳定性的影响.研究结果表明,后掠椭圆柱的迎风轴长度增加,会使横流定常涡的不稳定性增强;Reynolds数增大,使横流定常涡模态的不稳定性增强;不稳定性的强度与Reynolds数的大小为近似线性关系;飞行高度增加,Mach数变大,使横流定常涡的不稳定性变弱;后掠角在一定范围内的变化对横流定常涡的不稳定性影响不大.这些结果有助于提高对高空超音速飞行器翼前缘转捩机理的认识,为横流转捩预测提供理论指导     

Asymptotic Properties of the Markov Branching Process with Immigration

We consider the Markov branching process with immigration allowing the possibility of infinite numbers of offspring and/or immigrants. Our focus is on the construction and uniqueness of the minimal transition function and on its asymptotic behavior. Conditional limit theorems for the population size are given in cases for which the transition function is dishonest.