关于HBV及其药物相互作用的反应扩散方程的参数识别

研究具有反应-扩散现象的HBV及其药物相互作用系统的参数识别问题,依该系统正问题解的性质,建立了参数识别问题的数学模型,论证了系统正问题解关于待识别参数的连续依赖性与参数识别问题最优解的存在性.     

具有不确定参数二次自治系统的自适应同步问题研究

研究了两个带有参数的n维二次自治系统的自适应同步问题.根据Lyapunov稳定性理论及自适应控制方法得到了两个带有不确定参数非线性系统状态的渐近同步自适应控制方法.同时,识别了不确定参数.通过对两个超混沌系统的理论研究,证明了给定的非线性动力系统同步策略和参数识别的可行性.     

三维种群生态动力系统的参数识别

研究具有反应一扩散现象的三维种群生态动力系统的参数识别问题，依该系统正问题解的性质，建立了参数识别的数学模型；论证了系统正问题解关于待识别参数的连续依赖性与参数识别问题最优解的存在性。     

牵制控制含噪声的多延迟超网络的结构识别

本文研究了含噪声的多延迟超网络的结构识别问题,利用随机微分时滞方程的LaSalle不变原理和Lyapunov稳定性理论,获得了通过牵制控制进行超网络结构辨识的理论.通过数值仿真验证了理论结果的有效性.以三层网络为例,仅控制一个节点就可以成功识别出该网络的未知拓扑结构,同时,驱动网络和响应网络达到了同步.     

动力学方程组中参数识别模型及其优化性质

本文建立了动力学方程组中参数优化识别的数学模型.这是个含有动态约束的泛函极小化问题.应用线性算子的连续性,证明了该问题最优解的存在性,即参数的可识别性.最后依据弱Gateaux微分,给出并证明达到最优解的一个必要条件.     

空间一维结构分布动载荷时域识别方法

提出一种适用于空间一维结构分布动载荷的时域识别方法.基于空间分段和时间分段的思想, 推导了载荷时程识别的公式和过程.用MATLAB编写了载荷识别程序,以受分布动载荷简支梁和受随机风载荷输电导线的载荷识别对方法和程序进行验证, 并通过仿真试验研究了噪声对载荷识别的影响.结果表明,该方法对于线性问题有很高的识别精度,对于弱非线性问题能够满足工程应用要求,为分布动载荷时域识别提供了有效的途径.     

二元一般指数分布的识别性及其参数估计

讨论了一般二元指数分布的识别性问题及参数估计问题.本文证明了两个结论:其一、当只有最大值随机变量的分布已知时,仅一个参数可识别;其二、当可识别最大值的分布已知时,所有参数皆可识别.进一步根据上述结论得到了所有参数的最大似然估计.     

一类弱耦合动力系统的参数识别问题

研究一类弱耦合反应－扩散动力系统的参数识别问题。通过构造上下解，证明了反应－扩散方程组解的存在惟一性；给出了求解参数识别问题的最优化系，从而可以选取适当的梯度法或者共轭梯度法，实现对系统参数的识别。     

短基因编码序列识别及基因突变检测问题研究

基于频谱分析的基因预测方法普遍有一个缺点就是对短编码序列识别效果不佳,采用多参数Z-curve方法,再运用Fisher线性判别法对短编码序列(<100bp)进行预测,并进行了仿真验证.接着对基因突变问题采用频谱和信噪比分析方法的可行性进行了研究.     

软计算与硬计算融合的含油性属性与样本约简

随着石油勘探领域的不断扩大,含油性识别的研究对象也越来越复杂,传统的基于单一硬计算或软计算的方法在含油性识别中面临着严峻挑战.首先提出了软计算与硬计算融合的4种模式,然后运用GA-FCM对含油性的测井属性进行约简,将约简后的测井属性结合软计算与硬计算融合的分离模式对某油田Oilsk81,Oilsk83,Oilsk85三口井进行含油性模式识别,去掉出错率较高的样本,达到样本约简的目的;最后利用判别分析法对约简后的样本集进行检验分析.实验表明:第一,在这几个油区可以用声波时差和含油饱和度两个测井属性进行含油性识别;第二,将出错率高的样本进行约简可以提高样本集识别的正确率.     

Existence of optimal solution and optimality condition for parameter identification of an ecological species system

Parameter identification problem of a three species (predator, mutualist-prey, and mutualist) ecological system with reaction-diffusion phenomenon is investigated in this paper. The mathematical model of the parameter identification problem is constructed and continuous dependence of the solution for the direct problem on the parameters identified is obtained. Finally, the existence of optimal solution and an optimality necessary condition for the parameter identification problem are given.     

一类非光滑分布参数系统的可辨识性及最优性条件

变压器温度场参数辨识问题是一种分片光滑的分布参数辨识问题,以流速为辨识参数,针对传质传热的一类分布参数系统参数辨识问题,证明了系统最优参数的存在性和控制参数为最优的必要条件,为变压器温度场的数值模拟研究提供了理论基础.     

Distributionally robust parameter identification of a time-delay dynamical system with stochastic measurements

In this paper, we consider a parameter identification problem involving a time-delay dynamical system, in which the measured data are stochastic variable. However, the probability distribution of this stochastic variable is not available and the only information we have is its first moment. This problem is formulated as a distributionally robust parameter identification problem governed by a time-delay dynamical system. Using duality theory of linear optimization in a probability space, the distributionally robust parameter identification problem, which is a bi-level optimization problem, is transformed into a single-level optimization problem with a semi-infinite constraint. By applying problem transformation and smoothing techniques, the semi-infinite constraint is approximated by a smooth constraint and the convergence of the smooth approximation method is established. Then, the gradients of the cost and constraint functions with respect to time-delay and parameters are derived. On this basis, a gradient-based optimization method for solving the transformed problem is developed. Finally, we present an example, arising in practical fermentation process, to illustrate the applicability of the proposed method.     

Stability of the space identification problem for the elliptic‐telegraph differential equation

The present paper is devoted to study the space identification problem for the elliptic‐telegraph differential equation in Hilbert spaces with the self‐adjoint positive definite operator. The main theorem on the stability of the space identification problem for the elliptic‐telegraph differential equation is proved. In applications, theorems on the stability of three source identification problems for one dimensional with nonlocal conditions and multidimensional elliptic‐telegraph differential equations are established.     

On the stable difference scheme for source identification nonlocal elliptic problem

Approximation of source identification problem for elliptic equation with integral-type nonlocal condition is discussed. The first order of accuracy difference scheme for elliptic nonlocal identification problem is studied. By using spectral resolution of a self-adjoint operator, we establish stability inequalities for solution of constructed scheme. Subsequently, the difference scheme for approximate solution of multidimensional boundary value problem with integral-type nonlocal and first kind boundary conditions is investigated on stability. Numerical test examples are presented.     

An efficient method for solving an inverse problem for the Richards equation

A parameter identification problem for the hydraulic properties of porous media is considered. Numerically, this inverse problem is solved by minimizing an output least-squares functional. The unknown hydraulic properties which are nonlinear coefficients of a partial differential equation are approximated by spline functions. The identification is embedded into a multi-level algorithm and coupled with a linear sensitivity analysis to describe the ill-posedness of the inverse problem.     

Identification of Parameters of Nonlinear Dynamical Systems Simulated by Volterra Polynomials

We study the identification methods for the nonlinear dynamical systems described by Volterra series. One of the main problems in the dynamical system simulation is the problem of the choice of the parameters allowing the realization of a desired behavior of the system. If the structure of the model is identified in advance, then the solution to this problem closely resembles the identification problem of the system parameters. We also investigate the parameter identification of continuous and discrete nonlinear dynamical systems. The identification methods in the continuous case are based on application of the generalized Borel Theorem in combination with integral transformations. To investigate discrete systems, we use a discrete analog of the generalized Borel Theorem in conjunction with discrete transformations. Using model examples, we illustrate the application of the developed methods for simulation of systems with specified characteristics.     

Unilateral Crack Identification: A Filter-Driven, Iterative, Boundary Element Approach

An identification problem for parametric variational inequalities and linear com-plementarity problems is solved here by means of iterative filter techniques. A concrete application in engineering mechanics, the unilateral crack identification problem, is solved. The elastic contact problem is formulated by boundary element-linear complementarity techniques. By means of numerical results and comparison with previous approaches based on optimization and neural networks it is shown that this method is advantageous. In view of the difficulty of the considered bilevel optimization problem, this approach may be of interest for other applications as well.     

Robust Solution to Fuzzy Identification Problem with Uncertain Data by Regularization

This study considers the robust identification of the parameters describing a Sugeno type fuzzy inference system with uncertain data. The objective is to minimize the worst-case residual error using a numerically efficient algorithm. The Sugeno type fuzzy systems are linear in consequent parameters but nonlinear in antecedent parameters. The robust consequent parameters identification problem can be formulated as second-order cone programming problem. The optimal solution of this second-order cone problem can be interpreted as solution of a Tikhonov regularization problem with a special choice of regularization parameter which is optimal for robustness (Ghaoui and Lebret (1997). SAIM Journal of Matrix Analysis and Applications 18, 1035–1064). The final regularized nonlinear optimization problem allowing simultaneous identification of antecedent and consequent parameters is solved iteratively using a generalized Gauss–Newton like method. To illustrate the approach, several simulation studies on numerical examples including the modelling of a spectral data function (one-dimensional benchmark example) is provided. The proposed robust fuzzy identification scheme has been applied to approximate the physical fitness of patients with a fuzzy expert system. The identified fuzzy expert system is shown to be capable of capturing the decisions (experiences) of a medical expert.