A new forecasting method of discrete dynamic system

Usually, a linear differential equation is used to represent continuous dynamic systems, but a linear difference equation is used to represent discrete dynamic systems. AGO is one of the most important characteristics of grey theory, and its main purpose is to reduce the random of data. A linear differential equation, instead of a linear difference equation, is used to replace the grey differential equation to analyze discrete systems in this paper. The k-order derivatives of 1-AGO data are calculated after cubic spline interpolation of them, and the model parameters are estimated by means of the deterministic convergence scheme. ARIMA models are used to analyze the leading indicator in advance, and Fourier series with suitably chosen values of parameters is used for fitting the leading indicator. The model presented in this paper is called Grey Dynamic Model GDM(1,1,1).     

基于趋势修正的灰预测模型优化研究

针对序列增长趋势不完全满足准指数规律时的灰色预测建模问题,提出基于GM(1,1)模型与序列增长趋势之间偏差修正的建模方法,将GM(1,1)模型还原式中的常数项作为灰变量处理,加入调整系数以缩小拟合值与实际值之间的增长趋势差异,利用灰色离散模型拟合调整系数的变化过程,将得到的调整系数拟合值带入原时间响应函数,进而得到趋势修正的原始序列拟合值;运用新的建模方法对南京市第三产业用电量进行拟合和预测,证明了方法有效提升了GM(1,1)建模精度,并且拟合序列和实际序列的灰色绝对关联度得到提高.     

奇异摄动初值问题的一致收敛有限差分法

通过一阶和二阶导数讨论了带小参数的线性二阶常微分方程的初值问题.在均匀网格上得出了带常数拟合因子的指数型拟合差分格式,给出了离散最大模意义上的一阶一致收敛性.文中给出了数值结果.     

关于抛物型方程离散流量的收敛性

关于用差分方法求解具有间断系数的二阶抛型方程的问题, Ａ．Ｈ． ＴＮＸＯＨＯＢ与 Ａ．Ａ．Ｃａｍａｐｃ　从１９６１年山开始曾经作过详尽的研究,他们的结果都总结在专著［２］中,有关的文献也可以在该书中找到．他们指出在系数间断点处附近的网格点上格式的截断误差为Ｏ（１）,但差分格式的解在极大意义下收敛于原微分方程的连续解．他们在构造差分格式,并论证其收敛性时,充分利用了原微分方程中流连续的性质,但是却没有讨论差分格式中的离散流量的收敛性．８０年代 Ｔ．Ａ． Ｍａｎｔｅｎｆｆｅｌ, Ａ．Ｂ． Ｗｈｉｔｅ, Ｊｒ…     

Reconstruction of the Linear Ordinary Differential System Based on Discrete Points

In this paper, we discuss an inverse problem, i.e., the reconstruction of a linear differential dynamic system from the given discrete data of the solution. We propose a model and a corresponding algorithm to recover the coefficient matrix of the differential system based on the normal vectors from the given discrete points, in order to avoid the problem of parameterization in curve fitting and approximation. We also give some theoretical analysis on our algorithm. When the data points are taken from the solution curve and the set composed of these data points is not degenerate, the coefficient matrix $A$ reconstructed by our algorithm is unique from the given discrete and noisefree data. We discuss the error bounds for the approximate coefficient matrix and the solution which are reconstructed by our algorithm. Numerical examples demonstrate the effectiveness of the algorithm.     

捕食模型高精度参数的估计

研究了捕食者模型在多种观测值条件下的非线性微分方程组参数拟合问题.首先利用龙格-库塔法进行微分方程数值计算,通过首次积分项变形建立线性回归方程,进行最小二乘拟合;其次,考虑到实验数据包含随机误差的扰动,引进正规方程组对模型进行误差分析;最后针对时间变量也出现误差,采用拉依达准则筛选,然后提出了一种较为简单的参数分段动态估计算法.     

ON LINEARIZED FINITE DIFFERENCE SIMULATION FOR THE MODEL OF NUCLEAR REACTOR DYNAMICS

1 hoeductIOuThe dynamics models of one--dimensional continuous medium nuclear reactor are the foelowing initial--boundary value problem of the formsubject to the innal conditionsand the boundary conditionsIn (1. 1), x denotes position along the reactor, which is regarded as a rod of length L, t denotes the time, u(t) the logarithm of the loud reactor POwer, v(x,t) the deviation of the temperature from equilibrium, a(x) the ratio of the temperature coefficient of reactivity to theynean life of…     

确定高精度参数问题

在航天器精确制导等高科技的实际问题中,必须高精度地估计模型中的大批参数,建立高精度的数学模型,考虑较简单的确定高精度参数问题:食饵-捕食者系统.对于绝大多数微分方程得不到解析解,尤其是非线性微分方程这样的情况,运用稳定性理论和常微分方程几何理论来分析该生态模型.在数据分析处理中,采用了大量优化算法,如灰色系统辩识方法,多项式曲线选阶及拟合算法,牛顿迭代法等等.最后,通过MATLAB仿真验证了本方法的可行性.     

Working with differential,functional and difference equations using functional networks

In this paper we first analyze the problem of equivalence of differential, functional and difference equations and give methods to move between them. We also introduce functional networks, a powerful alternative to neural networks, which allow neural functions to be different, multidimensional, multiargument and constrained by link connections, and use them for predicting values of magnitudes satisfying differential, functional and/or difference equations, and for obtaining the difference and differential equation associated with a set of data. The estimation of the differential or difference equation coefficients is done by simply solving systems of linear equations, in the cases of equally or unequally spaced or missing data points. Some examples of applications are given to illustrate the method.     

Symbolic computation of high order compact difference schemes for three dimensional linear elliptic partial differential equations with variable coefficients

We present a symbolic computation procedure for deriving various high order compact difference approximation schemes for certain three dimensional linear elliptic partial differential equations with variable coefficients. Based on the Maple software package, we approximate the leading terms in the truncation error of the Taylor series expansion of the governing equation and obtain a 19 point fourth order compact difference scheme for a general linear elliptic partial differential equation. A test problem is solved numerically to validate the derived fourth order compact difference scheme. This symbolic derivation method is simple and can be easily used to derive high order difference approximation schemes for other similar linear elliptic partial differential equations.     

On the Numerical Solution to a Nonlinear Wave Equation Associated with the First Painlev′e Equation: an Operator-Splitting Approach

The main goal of this article is to discuss the numerical solution to a nonlinear wave equation associated with the first of the celebrated Painlevé transcendent ordinary differential equations. In order to solve numerically the above equation, whose solutions blow up in finite time, the authors advocate a numerical methodology based on the Strang’s symmetrized operator-splitting scheme. With this approach, one can decouple nonlinearity and differential operators, leading to the alternate solution at every time step of the equation as follows: (i) The first Painlevé ordinary differential equation, (ii) a linear wave equation with a constant coefficient. Assuming that the space dimension is two, the authors consider a fully discrete variant of the above scheme, where the space-time discretization of the linear wave equation sub-steps is achieved via a Galerkin/finite element space approximation combined with a second order accurate centered time discretization scheme. To handle the nonlinear sub-steps, a second order accurate centered explicit time discretization scheme with adaptively variable time step is used, in order to follow accurately the fast dynamic of the solution before it blows up. The results of numerical experiments are presented for different coefficients and boundary conditions. They show that the above methodology is robust and describes fairly accurately the evolution of a rather “violent” phenomenon.     

Stability criteria for differential equations with variable time delays

Time delays are an important aspect of mathematical modelling, but often result in highly complicated equations which are difficult to treat analytically. In this paper it is shown how careful application of certain undergraduate tools such as the Method of Steps and the Principle of the Argument can yield significant results. Certain delay differential equations arising in population dynamics may serve as good teaching examples for these methods. The determination of linear stability properties for an ordinary differential equation with a varying time delay is carried out through discrete point analysis, either by seeking explicit solutions or leading to the consideration of a difference equation and the roots of a characteristic polynomial. Numerical simulations carried out using MATLAB Simulink are compared to the analytical solutions, and computation is also used to suggest extensions to some results.     

Mathieu equation with application to analysis of dynamic characteristics of resonant inertial sensors

In this paper, Mathieu equation is applied to analyze the dynamic characteristics of resonant inertial sensors. Unlike previous work, Mathieu equation is not just a differential equation and analyzes the stability of the transition curves, but become an important method in analyzing parametric resonant characteristics and approximate output of resonant inertial sensors. It is demonstrated that the mathematical model of resonant inertial sensors is described by Mathieu equation. The relevant Mathieu equation theory and dynamic characteristics analysis methods were proposed, which include both stability and dynamic linear output. Finally, theoretical and experimental analysis show that the correlation of the theoretical curve and the experimental result coincide so perfectly, which means proposed analysis methods for Mathieu equation could be used to analyze the dynamic output characteristic of resonant inertial sensors. The theoretical analyzing approach of Mathieu equation and experimental results of resonant inertial sensors are obtained, which provide an application area for Mathieu equation and a reference for the robust design for resonant inertial sensors.     

Transforms from differential equations to difference equations and vice-versa applied to computer control systems

This letter derives the transform relationship between differential equations to difference equations and vice-versa, applied to computer control systems. The key is to obtain the rational fraction transfer function model of a time-invariant linear differential equation system, using the Laplace transform, and to obtain the impulse transfer function model of a time-invariant linear difference equation, using the shift operator. Finally, we find the discrete-time models of the first-order, second-order and third-order systems from their continuous-time models and vice-versa and find the mapping relationship between the coefficients of discrete-time models and the continuous-time models using the bilinear transform. An example is provided to demonstrate the proposed model transform methods.     

Representations of orthogonal polynomials

Zeilberger's algorithm provides a method to compute recurrence and differential equations from given hypergeometric series representations, and an adaption of Almquist and Zeilberger computers recurrence and differential equations for hyperexponential integrals. Further versions of this algorithm allow the computation of recurrence and differential equations from Rodrigues type formulas and from generating functions. In particular, these algorithms can be used to compute the differential/difference and recurrence equations for the classical continuous and discrete orthogonal polynomials from their hypergeometric representations, and from their Rodrigues representations and generating functions.In recent work, we used an explicit formula for the recurrence equation of families of classical continuous and discrete orthogonal polynomials, in terms of the coefficients of their differential/difference equations, to give an algorithm to identify the polynomial system from a given recurrence equation.In this article we extend these results by presenting a collection of algorithms with which any of the conversions between the differential/difference equation, the hypergeometric representation, and the recurrence equation is possible.The main technique is again to use explicit formulas for structural identities of the given polynomial systems.     

Modeling and parameter identification of a maltodextrin DE 12 drying process in a convection oven

The drying kinetics of maltodextrin DE 12 in a convection oven are modeled using Fick's second law of diffusion and following the William, Landel and Ferry (WLF) equation for the moisture and temperature dependence of the effective diffusivity. An experimental design with a temperature range from 70°C to 140°C and sample amount varying from 4 to 12 ml is used. The resulting diffusion equation describing the dynamics of moisture content is highly nonlinear and possesses Dirichlet and Neumann boundary conditions. Ordinary differential equations are added to take the time-dependent variation of temperature into account. The method of lines is applied to discretize the partial differential equation w.r.t. the space variable leading to a highly stiff and numerically unstable system of ordinary differential equations. The data fitting problem is formulated to estimate some unknown model parameters simultaneously for 18 data sets under consideration.     

灰色GM(1,1,k,k2)模型背景值及时间响应函数优化

本文提出了一种新的带有时间幂次项的灰色GM(1,1,k,k²)模型,给出了其灰微分方程和白化微分方程基本形式。基于最小二乘法获得了该模型参数估计值,并推导了该模型时间响应函数。鉴于GM(1,1,k,k²)模型灰微分方程与白化微分方程之间存在跳跃关系,首先对灰微分方程的背景值进行了优化,并推导了优化后的背景值计算公式。为了克服初始值的影响,根据误差平方和最小,进一步优化了GM(1,1,k,k²)模型时间响应函数。最后,该优化后的GM(1,1,k,k²)模型被应用于软土地基沉降预测,获得了较好的模拟预测效果,说明模型是可行的。     

灰色离散序列增量动态GML(n,1)模型的参数辩识方法及应用

基于灰色 GM( n,1 )微分动态建模原理 ,按离散数据序列特点 ,提出灰色离散时间序列增量动态GML( n,1 )模型及初次、二次参数辩识方法 .GML( n,1 )模型的信息包容量丰富 ,适用范围广泛 .     

Relationship between spectral and coefficient criteria of mean-square stability for systems of linear stochastic differential and difference equations

We establish the relationship (equivalence) between the spectral and algebraic (coefficient) criteria (the latter is represented in terms of the Sylvester matrix algebraic equation) of mean-square asymptotic stability for three classes of systems of linear equations with varying random perturbations of coefficients, namely, the ltô differential stochastic equations, difference stochastic equations with discrete time, and difference stochastic equations with continuous time.