一个最优的模糊逼近器

In a dot product space with the reproducing kernel (r. k. S. ) ,a fuzzy system with the estimation approximation errors is proposed ,which overcomes the defect that the existing fuzzy control system is difficult to estimate the errors of approximation for a desired function,and keeps the characteristics of fuzzy system as an inference approach. The structure of the new fuzzy approximator benefits a course got by other means.     

基于有理函数模型的一维最优化方法

在本文中提出了基于有理函数模型的一维最优化方法。这些方法比二次模型方法有较好的数值性态和适应性。我们给出了有理反差商方法和Ｎｅｖｉｌｅ型方法，并将其与二次插值方法进行了数值比较。     

大型稀疏无约束最优化的列分划校正Cholesky因子算法

我们考虑求解无约束优化问题1引言(?)f(x),(1)其中f：D(?)R~n→R为R~n上的二次连续可微函数,且f(x)的二阶Hesse阵H(x)稀疏、正定．为了求解问题(1),我们考虑下列Newton型方法x~(k 1)=x~k-(B~k)~(-1)▽f(x~k),k=0,1,…,(2)其中B~k是和Hesse阵H(x~k)具有相同稀疏性的近似．由于Hesse阵对称,我们假定B~k对称．为了具体说明给定矩阵B的稀疏性,我们使用M来定义指标对(i,j)的集合,其     

The Global Convergence of Self-Scaling BFGS Algorithm with Nonmonotone Line Search for Unconstrained Nonconvex Optimization Problems

The self-scaling quasi-Newton method solves an unconstrained optimization problem by scaling the Hessian approximation matrix before it is updated at each iteration to avoid the possible large eigenvalues in the Hessian approximation matrices of the objective function. It has been proved in the literature that this method has the global and superlinear convergence when the objective function is convex （or even uniformly convex）. We propose to solve unconstrained nonconvex optimization problems by a self-scaling BFGS algorithm with nonmonotone linear search. Nonmonotone line search has been recognized in numerical practices as a competitive approach for solving large-scale nonlinear problems. We consider two different nonmonotone line search forms and study the global convergence of these nonmonotone self-scale BFGS algorithms. We prove that, under some weaker condition than that in the literature, both forms of the self-scaling BFGS algorithm are globally convergent for unconstrained nonconvex optimization problems.     

最大相关模糊查询及其应用研究

在文档类模糊查询方面进行了较深入的研究,首次提出并实现了间接相关全衰期和最大相关查询,其原理有别于传统字符串相等比率的模糊查询技术,采用相关性定义及最大相关传递模式,目的在于实现更广泛意义下的模糊查询。在适当定义相关度情形下,不但能够查找出传统模糊查询搜索到的内容,而且可以查找到字面上完全不同但意思相关的条文,最大相关传递模式能够使得词语之间的相关度按一定规则传递,因此更具一般性和实用性。     

高校应用数学学报

面对成比例交易成本的情况下外汇期权的定价；带常利率的Erlang（2）风险模型的罚金折现期望函数；具有反馈、不可靠服务台和二次多选择服务的M／G／1重试排队系统；解非线性优化问题的锥模型信赖域方法；基于非拟牛顿方法无约束最优化问题的全局收敛性；具有分片线性NCP函数的QP-free可行域方法。     

TESTING DIFFERENT CONJUGATE GRADIENT METHODS FOR LARGE—SCALE UNCONSTRAINED OPTIMIZATION

In this PaPer we test different conjugate gradient (CG) methods for solving large-scale unconstrained optimization problems.The methods are divided in two groups:the first group includes five basic CG methods and the second five hybrid CG methods.A collection of medium-scale and large-scale test problems are drawn from a standard code of test problems.CUTE.The conjugate gradient methods are ranked according to the numerical results.Some remarks are given.     

Ag/AAO纳米有序阵列复合结构等效光学参量的确定

引入厚度偏差Δd, 修正了薄膜透射率表达式.基于Ag/AAO纳米有序阵列复合结构实验透射光谱(500—2700nm)的两条极值包络线, 定义了一个优化函数, 结合最优化数值算法尝试确定具有较强吸收的Ag/AAO纳米有序阵列复合结构的等效光学参量. 由此计算了该结构的等效折射率n、等效消光系数k、平均等效厚度d以及厚度偏差Δd. 该方法对Ag/AAO纳米复合结构平均等效厚度的相对计算误差仅为0.3%, 与实测厚度基本一致, 且Ag/AAO纳米复合结构的模拟透射谱与实验透射光谱在500—2700nm波段范围内相符. 这表明该计算方法可有效确定Ag/AAO纳米复合结构的等效光学参量, 并与实验结果是自洽的. 关键词： 薄膜光学 光学参量 纳米复合结构 最优化算法     

组合最优化中的布尔方法

本文旨在从NP-完全性理论的角度,以拟布尔函数最优化为典型实例介绍组合最优化问题的一些研究方法和取得的主要进展。并且也提出了一些有待解决的问题和可能的研究途径。