基于相空间重构的一阶加权局域预测法在溶解氧预测中的应用

将混沌理论引入到水质预测中,分析海河溶解氧时间序列,进行相空间重构和计算最大Lyapunov指数.结果表明,海河溶解氧时间序列具有混沌特性,可以对其进行短期预测.在此基础上,应用一阶加权局域预测模型进行了预测,预测结果具有一定的精度,为水质预测研究提供了新的思路.     

基于相空间重构技术的金融系统混沌识别

借助工程技术领域内识别非线性系统混沌现象的相空间重构技术研究了金融混沌的识别问题.以我国金融系统历经本轮全球金融危机这个金融史上影响最为严重的金融混沌为研究对象;研究发现:在全球金融危机的冲击下,我国金融系统在运行过程中发生了确定性的失稳,出现了金融混沌现象.从而为进一步防范与控制金融混沌奠定基础.     

A New Approach to the Algebraic Structures for Integration Methods

The analysis of compositions of Runge-Kutta methods involves manipulations of functions defined on rooted trees. Existing formulations due to Butcher [1972], Hairer and Wanner [1974], and Murua and Sanz-Serna [1999], while equivalent, differ in details. The subject of the present paper is a new recursive formulation of the composition rules. This both simplifies and extends the existing approaches. Instead of using the order conditions based on trees, we propose the construction of the order conditions using a suitably chosen basis on the tree space. In particular, the linear structure of the tree space gives a representation of the C and D simplifying assumptions on trees which is not restricted to Runge-Kutta methods. A proof of the group structure of the set of elementary weight functions satisfying the D simplifying assumptions is also given is this paper.     

基于改进C-C方法相空间重构和LS-SVM的隧道拱顶沉降预测模型

在地铁工程的设计、施工、工后沉降控制过程中,拱顶下沉监测值是反映地下工程结构安全和稳定的重要数据.针对常用的地铁拱顶沉降测模型只能做短期预测,精度不高,且需要一些土的本构参数的问题,将相空间重构、最小二乘支持向量机理论相耦合,建立基于改进C-C方法相空间重构和最小二乘支持向量机的地铁隧洞拱顶沉降混沌时间序列预测模型.经实例演算,模型比传统C-C方法相空间重构、基于最大Lyapunov指数的混沌预测模型、人工神经网络模型拟合效果好,预测精度高.     

Poverty Level of Households: A Multidimensional Approach Based on Fuzzy Mathematics

In recent years, extensive research jobs have been developed on the definition, measurement and analyzing of poverty. Poverty is a multidimensional phenomenon, thus a number of challenges appears measuring it. The fuzzy set theoretic approach has been used to measure the poverty and to classify the difference between poor and non-poor households. This paper aims at proposing a new methodology to measure the poverty index in fuzzy environment via a two-step membership function. The concept of one poverty line is chalked out first and then a general method is developed to split the poverty index. Linguistic variables are used for the attributes to find the membership values of the households against the attributes and to grade the attributes. The effectiveness and usefulness of the proposed method is numerically illustrated through a case study for rural household people living in remote rural areas of India.     

基于可信性分布的投资组合问题的一种混合智能方法

研究了模糊环境下基于效用函数的有效资产投资组合的收益率模型,模型建立在可信性分布的基础上,而不是概率分布或可能性分布基础上.给出模糊环境下基于可信性分布的n种资产的最优投资组合问题的混合智能算法以寻找某种效用函数意义下的最优组合.并以实例仿真说明该方法的有效性.     

依赖凝聚函数求解非线性互补问题的一种微分方程方法

利用凝聚函数一致逼近非光滑极大值函数的性质,将非线性互补问题转化为参数化光滑方程组.然后,对此方程组给出了一种微分方程解法,并且证明了非线性互补问题的解是微分方程系统的渐进稳定平衡点.在适当的假设条件下,证明了所给出的算法具有二次收敛速度.数值结果表明了此算法的有效性.     

工程项目投资方案评价方法的研究-基于广义λ-Shapley Choquet积分

随着社会的发展,工程项目投资方案选择所受的影响因素越来越多。方案的属性值呈现出不确定性、模糊性的特征。文章对工程项目投资方案的主要影响因素进行了系统全面的分析,构造出影响因素的指标体系(即属性集)。为应对不确定信息和降低决策者的决策难度,让决策者利用所构建的语言变量给出方案属性值的定性判断,然后利用所构建的语言变量和三角模糊数之间的对应关系,将其转化为相应的三角模糊数,从而得到相应的定量模糊判断。为得到最优的综合投资方案,同时考虑属性间的交互作用,文章利用非可加测度及广义λ-Shapley Choquet积分来计算投资方案的综合评价值,属性权重由广义Shapley函数确定。基于此,给出了工程项目投资方案选择的一个新评价方法。最后,通过一个实际案例分析来验证所给方法的可行性和有效性。     

方差分析平方和分解分析方法的一种新形式——数理统计方差分析教学的一种新方法

给出了不同于其他教材的平方和分解形式,它可以更为直观地证明和得到方差分析所需检验统计量的分布.     

Cn中全纯函数空间上乘子特征的一种刻划

在C^n中单位球上根据p,q的不同范围给出了Bloch型空间β^p和β^q之间函数乘子的一种新的刻划,并刻划了Lipschitz空间之间以及Lipschitz空间到Bloch空间的函数乘子,拓广了Bloch空间的乘子理论．     

基于对象-属性空间分割技术的企业员工技能与知识体系构建方法

针对企业员工技能知识点确定及其与企业员工人员的针对性分类划分问题,提出了一种基于对象一属性空间分割技术的企业技能与知识体系构建方法。方法基于角色一业务活动矩阵和业务活动技能知识矩阵导出角色一技能知识矩阵,然后应用对象-属性空间分割技术最终得出合理的技能知识体系。     

A Complete Classification of the Simultaneously Bireflective and Bicoreflective Subconstructs of Approach Spaces

In this paper, using a technique developed by Herrlich and Lowen [3], we classify and describe all subconstructs of A P, the construct of approach spaces, which are at the same time bireflective and bicoreflective in A P.     

A minimum average risk approach to shrinkage estimators of the normal mean

For the problem of estimating the normal mean based on a random sample X ₁,...,X _n when a prior value ₀ is available, a class of shrinkage estimators % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaGaeyypa0Jaam4AaiaacIcadaqfqaqabKqaahaacaqGUb% aaleqaneaacaqGubaaaOGaaiykaiaabccadaqfqaqabKqaahaacaWG% UbaaleqaneaaceqGybGbaebaaaGccaqGGaGaey4kaSIaaeiiaiaacI% cacaaIXaGaaeiiaiabgkHiTiaabccacaWGRbGaaiikamaavababeqc% baCaaiaab6gaaSqab0qaaiaabsfaaaGccaGGPaGaaiykamaavababe% qcbaCaaiaad6gaaSqab0qaaiabeY7aTbaaaaa!5615!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k) = k(\mathop {\rm{T}}\nolimits_{\rm{n}} ){\rm{ }}\mathop {{\rm{\bar X}}}\nolimits_n {\rm{ }} + {\rm{ }}(1{\rm{ }} - {\rm{ }}k(\mathop {\rm{T}}\nolimits_{\rm{n}} ))\mathop \mu \nolimits_n \] is considered, where % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqcdawaaiaadsfaaaGccaqGGaGaaeypaiaabcca% caWGUbWaaWbaaSqabeaacaaIXaGaai4laiaaikdaaaGccaGGOaWaa0% aaaeaacaWGybaaamaaBaaajeaWbaGaamOBaaWcbeaakiaabccacqGH% sislcaqGGaWaaubeaeqajeaWbaGaaGimaaWcbeqdbaGaaeiVdaaaki% aacMcacaqGGaGaae4laiabeccaGiabeo8aZbaa!4C33!\[\mathop T\nolimits_n {\rm{ = }}n^{1/2} (\overline X _n {\rm{ }} - {\rm{ }}\mathop {\rm{\mu }}\nolimits_0 ){\rm{ /}} \sigma \] and k is a weight function. For certain choices of k, % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] coincides with previously studied preliminary test and shrinkage estimators. We consider choosing k from a natural non-parametric family of weight functions so as to minimize average risk relative to a specified prior p. We study how, by varying p, the MSE efficiency (relative to \-X) properties of % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] can be controlled. In the process, a certain robustness property of the usual family of posterior mean estimators, corresponding to the conjugate normal priors, is observed.     

基于支持向量机的混沌时间序列模型在房产价格指数预测中的应用

针对房产价格指数的预测问题,建立了混沌时间序列的支持向量机的非线性预测模型.首先运用Cao氏法进行相空间重构,并利用改进型小数据量法计算最大的Lyapunov指数,分析上海房产价格指数时间序列的混沌特性.然后以最小嵌入维数作为支持向量机的输入节点,建立房地价格指数的预测模型.实例表明,该方法能较好地处理复杂的房地产数据,具有较高的泛化能力和很好的预测精度.     

A Variational Approach to the Denoising of Images Based on Different Variants of the TV-Regularization

We discuss several variants of the TV-regularization model used in image recovery. The proposed alternatives are either of nearly linear growth or even of linear growth, but with some weak ellipticity properties. The main feature of the paper is the investigation of the analytic properties of the corresponding solutions.     

A Fixed Point Approach to the Fuzzy Stability of a Mixed Typ e Functional Equation

Through the paper, a general solution of a mixed type functional equation in fuzzy Banach space is obtained and by using the fixed point method a generalized Hyers-Ulam-Rassias stability of the mixed type functional equation in fuzzy Banach space is proved.     

关于“加权Hardy空间的分子刻画”的一个注记

给出了当 12

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