基于一阶预测有效度的IGOWLA算子模糊组合预测方法

文章针对预测对象具有模糊性的组合预测问题，用三角模糊数表征问题的特征信息，引入诱导广义有序加权对数平均(IGOWLA)算子的概念，以基于模糊信息的一阶预测有效度作为精度指标，建立基于一阶预测有效度的IGOWLA算子模糊组合预测的最优化模型，并通过实例分析说明了该模型能显著提高预测精度。     

基于模糊时间序列模型的CPI预测方法研究

构建模糊AR(p)时间序列模型,对CPI进行了预测,通过实际数据模拟发现,与传统的ARIMA模型相比,模糊AR(p)时间序列模型预测的效果更好.     

基于具有LR型模糊输出回归模型的保费预测

在保费预测研究中,提出了一种基于模糊回归模型的预测方法.采用模糊最小二乘法,针对清晰输入和LR型模糊输出,在考虑输出量隶属函数类型存在差异问题基础之上,得到模型回归系数的迭代解.通过最小二乘估计的定性分析,给出检验模型拟合度的指标.结合保费数据的预测结果表明模型可行且具有较强的解释能力.     

基于逆模糊数的模糊时间序列预测的新方法

Song和Chisson于1993年提出模糊时间序列预测理论.虽然至今已经提出许多模糊时间序列预测模型,但是迄今为止尚未给出预测未知年数据的模糊时间序列预测模型.提出基于逆模糊数的模糊时间序列预测的新方法该模型对广西大学已知的2001~2012年的注册数进行预测分析,平均预报误差率比相关文献的方法有所改善.还对广西大学未知的2013年和2014年注册数进行预测研究.方法是短期预测的一种模糊时间序列预测方法.     

一类不分明时间序列的回归预测

研究了一类不分明时间序列的线性回归预测问题,通过模糊数空间中的距离,建立了模糊环境中最小二乘回归模型,证明了回归模型解的存在性和唯一性,并给出了确定模型的模糊参数及检验模型拟合度的计算公式。     

基于信息熵的模糊物元模型预测玉米螟种群动态

利用模糊物元模型对玉米螟的种群动进行预测,在利用信息熵理论确定预报因子的权重的基础上构造了复合模糊物元模型,并根据往年资料构造出用于预测的关联度区间,以预测关联度映射的区间进行判决,这样避免了传统分级方法造成的主观误差,同时提高了预测的精度.     

基于灰模型的区间模糊数时间序列预测

研究了基于灰模型的二元区间和三角模糊数时间序列的预测方法.目前以GM(1,1)模型为代表的灰色预测模型只适用于精确数序列.改进了GM(1,1)模型的定义型方程中的参数形式,使方程能适用于几类常见区间模糊数序列.接着,基于区间模糊数的计算准则,分别具体给出了二元和三角模糊数GM(1,1)模型(BIFGM(1,1)和TFGM(1,1))的预测过程.模型对于区间模糊数的界点序列的发展系数进行了加权平均处理,以此保证了区间模糊数序列发展态势的整体性.最后进行了实例应用,验证了模型的有效性.     

基于逆模糊数的模糊时间序列预测的新方法北大核心

Song和Chisson于1993年提出模糊时间序列预测理论．虽然至今已经提出许多模糊时间序列预测模型,但是迄今为止尚未给出预测未知年数据的模糊时间序列预测模型．提出基于逆模糊数的模糊时间序列预测的新方法该模型对广西大学已知的2001-2012年的注册数进行预测分析,平均预报误差率比相关文献的方法有所改善．还对广西大学未知的2013年和2014年注册数进行预测研究．方法是短期预测的一种模糊时间序列预测方法．     

基于逆模糊数的模糊时间序列模型的农机总动力预测方法

提出一种改进的基于逆模糊数的新模糊时间序列预测模型.应用模型研究辽宁省农机总动力预测问题,比一元线性回归模型,二次移动平均模型,指数曲线模型,灰色理论GM(1,1)模型等4种模型和它们的组合模型的平均预测误差率AFER都有较大改善,是值得推荐的一种时间序列预测方法.     

基于DGM的模糊多目标区间预测

无论对预测过程还是决策过程,区间预测相对于点估计预测往往拥有更重要的信息量。本文基于模糊多目标规划模型和离散灰色模型理论(DGM),给出了基于DGM的模糊多目标区间预测模型。同时,为了有利于比较区间预测的优劣,又提出了评价区间预测优劣的两个指标:区间中心的均值相对百分比误差和区间边界的均值相对百分比误差。最后,将LCD TV销售量作为本模型的实验数据,给出了区间预测的结果,并将我们的结果与其他两个模型的预测结果进行了比较分析。     

有资格限制的指派问题的求解方法

在实际的指派工作中，常会遇到某个人有没有资格去承担某项工作的问题，因此，本建立了有资格限制的指派问题的数学模型。在此数学模型中，将效益矩阵转化为判定矩阵，由此给出了判定此种指派问题是否有解的方法；在有解的情况下，进一步将效益矩阵转化为求解矩阵，从而将有资格限制的指派问题化为传统的指派问题来求解。最后给出了一个数值例子来说明这样的处理方法是有效的。     

L－fuzzy集网的R－收敛性质

本文在ＬＦ拓扑空间中建立了Ｌ－ｆｕｚｚｙ集网的弱收敛（Ｒ－收敛）概念，应用文［４］中的Ｒ－闭包，系统讨论了它们的性质，证明了等式ＲｌｉｍＡ＿ｎ＝∧（∨Ａ＿ｍ）＿Ｒ和ＲｌｉｍＡ＿ｎ＝Ａ＿ｎ＝∧（∨Ａ＿ｍ）＿Ｒ并且给出了Ｌ－ｆｕｚｚｙ集网与其子网之间的关系。     

Estimation of the number of components of finite mixtures of multivariate distributions

An estimator of the number of components of a finite mixture ofk-dimensional distributions is given on the basis of a one-dimensional independent random sample obtained by a transformation of ak-dimensional independent random sample. A consistency of the estimator is shown. Some simulation results are given in a case of finite mixtures of two-dimensional normal distributions.     

Galois Structure of K-Groups of Rings of Integers

N/Kbe a Galois extension of number fields with finite Galois group G.We describe a new approach for constructing invariants of the G-module structure of the K groups of the ring of integers of N in the Grothendieck group of finitely generated projective Z[G]modules. In various cases we can relate these classes, and their function field counterparts, to the root number class of Fröhlich and Cassou-Noguès.     

On the R-Order of Convergence of a Family of Methods for Simultaneous Extraction of Part of All Roots of Algebraic Polynomials

This note deals with the R-order of convergence of Weierstrass-Durand-Kerner-Dochev type single-step methods for the simultaneous determination of only a part of all roots of algebraic polynomials.     

Convergence of densities of some functionals of Gaussian processes

The aim of this paper is to establish the uniform convergence of the densities of a sequence of random variables, which are functionals of an underlying Gaussian process, to a normal density. Precise estimates for the uniform distance are derived by using the techniques of Malliavin calculus, combined with Stein?s method for normal approximation. We need to assume some non-degeneracy conditions. First, the study is focused on random variables in a fixed Wiener chaos, and later, the results are extended to the uniform convergence of the derivatives of the densities and to the case of random vectors in some fixed chaos, which are uniformly non-degenerate in the sense of Malliavin calculus. Explicit upper bounds for the uniform norm are obtained for random variables in the second Wiener chaos, and an application to the convergence of densities of the least square estimator for the drift parameter in Ornstein–Uhlenbeck processes is discussed.     

Number of connected components of groups of real points of adjoint groups

We present a unified approach to compute the number of connected components in the group of real points of adjoint almost simple real algebraic groups.     

白骨化尸体死亡时间的推断

本文分析了15具白骨化尸体标本的股骨汞(Hg),铅(Pb),镉(Cd)元素含量数据,在三年的时间内采集了3次,一共收集到45个数据。首先将这组数据看着纵向数据,利用线性随机效应混合模型、Cox随机混合效应模型进行分析,结果显示,如果对每个白骨化尸体标本建立线性模型,可以精确预测出死亡时间,而且不需要采集铅元素含量数据。混合效应模型的预测效果也很好,最大误差不会超过1个月。其次我们对数据不作任何假设,利用机器学习中随机森林方法分析数据,并利用5折交叉验证方法来判断结果的可靠性,训练集和测试集的NMSE分别为0.1205944,0.5604286,因此可以用训练出的模型来预测死亡时间。     

Admissibility of estimators of the probability of unobserved outcomes

The problem of estimating the probability of unobserved outcomes or, as it is sometimes called, the conditional probability of a new species, is studied. Good's estimator, which is essentially the same as Robbins' estimator, namely the number of singleton species observed divided by the sample size, is studied from a decision theory point of view. The results obtained are as follows: (1) When the total number of different species is assumed bounded by some known number, Good's and Robbins' estimators are inadmissible for squared error loss. (2) If the number of different species can be infinite, Good's and Robbins' estimators are admissible for squared error loss. (3) Whereas Robbins' estimator is a UMVUE for theunconditional probability of a new species obtained in one extra sample point, Robbins' estimator is not a uniformly minimum mean squared error unbiased estimator of the conditional probability of a new species. This answers a question raised by Robbins. (4) It is shown that for Robbins' model and squared error loss, there are admissible Bayes estimators which do not depend only on a minimal sufficient statistic. A discussion of interpretations and significance of the results is offered. Research supported by NSF Grant DMS-88-22622.     

Groups of Automorphisms of Tournaments

By the Holland Representation Theorem, every lattice ordered group (l-group) is isomorphic to a subalgebra of the l-group of automorphisms of a chain. Since weakly associative lattice groups (wal-groups) and tournaments are non-transitive generalizations of l-groups and chains, respectively, the problem concerning the possibility of representation of wal-groups by automorphisms of tournaments arises. In the paper we describe the class of wal-groups isomorphic to wal-groups of automorphisms of tournament and show some of its properties.