一种基于模糊集值统计的集对预测方法

在集对分析中,差异度系数i是体现系统不确定性的重要变量,但如何取值一直在理论上没有解决,本文根据i的取值的不确定性与模糊性,提出了一种基于模糊集值统计的差异度系数取值方法.对于原始数据中的噪声,本文提出了一种基于模糊软阈值的小波去噪方法,并利用支持向量回归方法来进行同异反预测,在一定程度上克服了线性建模技术的不足.此外,为了克服同一度、差异度与对立度之间的归一化约束,本文还提出了一种熵变换的方法.     

联系数在梯形模糊数多属性决策中的应用

属性权重和属性值都是梯形模糊数的多属性决策问题是一种带有不确定性的决策,需要作不确定性分析后才能得出结论.为此把梯形模糊数表示的属性值和属性权重先用其特征函数"均值+偏差"联系数(特征联系数)表示,再利用联系数运算法则作"加权求和"运算,不仅获得与其它决策方法相同的结果,而且借助联系数中i的不同取值考察决策对象的排序变化,方法简便易行,且具有较强适用性.     

图的色多项式系数之和问题的研究

本文给出了任何简单图G(V,E)的色多项式P(G，λ)=∑i=1^vαiλ^i系数之和的公式：∑i=1^vαi={0ε≠0 1ε=0;并进行了证明，从而为判别一个多项式不是图的色多项式提供了一个必要条件．同时也分别给出了树、2-树、圈、轮图和完全图的色多项式系数绝对值之和的表达式．最后证明了任何简单连通图的色多项式系数绝对值之和∑i=1^v|αi|与边ε成正比，且必满足2^v-1≤∑i=1^v|αi|≤пi=1^vi．     

灰色关联度分析在投入产出关联度中的应用

产业经济学常用投入产出方法中的影响力系数和感应度系数来评价部门的拉动和推动作用,从而作为确定国民经济中关键部门最重要的参考指标。本文针对影响力系数和感应度系数的缺陷,采用灰色关联度曲线相似的思想对中国1997年17部门的投入产出表作了实证分析,并和传统的方法作了比较,结果表明,用本方法确定关键部门更符合实际,具有重要的参考价值。     

多项式{k∑i=0t^i}^n系数的性质

本讨论了多项式{k∑i=0t^i}^n的系数的一些性质,得出了一些有趣的结果。     

半变系数模型PLS估计的渐近正态性

半变系数模型在统计建模中具有重要的应用．最近几年，人们提出了许多方法来估计其常系数和函数系数，但是估计的渐近性质还没有被系统的研究．本文介绍了半变系数模型的PLS估计，在Fan和Huang对常系数渐近性质研究的基础上，给出了函数系数的渐近正态性。     

主成分分析法在产业关联度研究中的应用

在产业经济学中，影响力系数和感应度系数是常用的评价产业部门拉动作用和推动作用的方法。本文针对影响力系数和感应度系数的缺陷，采用主成分分析法对投入产出表中的完全消耗系数进行研究，分析产业关联度，以确定国民经济主导产业。最后以中国1997年投入产出表为例进行了分析。结果表明，本方法更加符合实际，具有重要的参考价值。     

变系数再生散度线性模型和它的估计

本文研究了一类变系数再生散度线性模型.利用局部最大似然的方法,得到了兴趣参数的估计,同时也研究了局部权和光滑参数的确定以及统计推断,结果推广了文献[11]的工作.     

关于多项式系数的整除性

设 n是正整数 ,k1 ,k2 ,… ,ks 是适合 k1 +k2 +… +ks=n的非负整数 ,正整数 nk1 k2 … ks=n!k1 !k2 !… ks!称为多项式系数 .本文讨论了当n=a0 +a1 p+a2 p2 +… +arpr ,其中 p为素数且 p≤ n,0≤ ai相似文献   

"兰氏"平方律作战毁伤过程兵力损耗率系数战例求解理论

如何求得著名的“兰氏”平方律战斗动力学方程中双方兵力损耗率系数，这是作战模拟应用研究领域中一个久攻未克的难题。本文提出了以作战结果来逆向研究作战过程中双方兵力损耗率系数的思想。阐述了对于不变的作战双方在相同（相近）的作战环境与作战条件下相继进行的作战序列里，双方各自的兵力损耗率系数不变（波动不大）的公理，论证了揭示作战序列内部规律的两条定理。据此，建立了兵力损耗率系数的战例求解理论与方法。运用这一理论与方法，据以往发生的作战过程其数值特征可以求得未来相似或相同作战过程中双方兵力损耗率系数的具体取值，首次解决了作战模拟研究领域中兵力损耗率系数的具体取值这一难题。     

Stationary and multi-self-similar random fields with stochastic volatility

This paper introduces stationary and multi-self-similar random fields which account for stochastic volatility and have type G marginal law. The stationary random fields are constructed using volatility modulated mixed moving average (MA) fields and their probabilistic properties are discussed. Also, two methods for parameterizing the weight functions in the MA representation are presented: one method is based on Fourier techniques and aims at reproducing a given correlation structure, the other method is based on ideas from stochastic partial differential equations. Moreover, using a generalized Lamperti transform we construct volatility modulated multi-self-similar random fields which have type G distribution.     

The double pivot simplex method

The simplex method, created by George Dantzig, optimally solves a linear program by pivoting. Dantzig’s pivots move from a basic feasible solution to a different basic feasible solution by exchanging exactly one basic variable with a nonbasic variable. This paper introduces the double pivot simplex method, which can transition between basic feasible solutions using two variables instead of one. Double pivots are performed by identifying the optimal basis in a two variable linear program using a new method called the slope algorithm. The slope algorithm is fast and allows an iteration of DPSM to have the same theoretical running time as an iteration of the simplex method. Computational experiments demonstrate that DPSM decreases the average number of pivots by approximately 41% on a small set of benchmark instances.     

半赋权向量与高阶加权平均值及其在宏观经济分析中的应用

本文提出了半赋权向量概念 ,讨论了高阶加权均方矩的平均值性质 ,运用半赋权向量的性质推出了高阶加权平均值的一些性质 .本文还介绍了半赋权向量与高阶加权平均值在宏观经济分析中的应用 ,讨论了其应用前景 .     

估计极端行为模型:分位数回归方法及其实现与应用

在许多社会和管理研究中,研究者通常很感兴趣不同于期望或平均的极端行为的理论解释。这些特殊个案所包含的信息往往是研究的创新点和解决某些问题的突破口,但传统的最小平方法与最小一乘法并不适宜于这类研究问题的解决。本文讨论一种估计极端行为的理想模型:分位数回归。本文在对分位数回归的国内外研究现状进行综述后,介绍了分位数回归的模型和实现方法,并将它与最小平方法、最小一乘法进行了比较。最后探讨它在我国管理研究领域的应用方式和有关条件。     

固定合作规模网络的平均路径长度

本文提出了一种特殊的合作网络,称之为固定合作规模网络．我们重点研究了这类网络的平均路径长度,通过建立微分方程,得到平均路径长度的增加速度近似与网络规模的对数成正比．     

Modified offensive earned-run average with steal effect for baseball

This short article introduces and studies a modified offensive earned-run average (MOERA) index which is based on a stationary Markov chain and evaluates the contribution of a player in baseball. An original offensive earned-run average (OERA) index does not consider the effect of stealing. The MOERA index proposed here includes the effect. Some examples are presented for Japanese professional baseball players.     

Optimization of technology parameters for the plane-strain component in the process of gas quenching

The paper introduces an optimization method for the technology parameters of the plane-strain component in the process of gas quenching. Distortion, residual stress, average surface hardness and standard deviation of surface hardness are regarded as the optimization objectives. A new heat transfer coefficient model is presented, five distinct heat transfer coefficients are used at various regions of the model. The five heat transfer coefficients are regarded as the design variables, and four regressive equations are established by using response surface method. The four equations, respectively represent the relations between the four optimization objectives and the design variables. A multi-objectives optimization model is established, and the multi-objectives optimization model is optimized by the non-linear method. The optimized technology parameters are used to simulate the gas quenching process by FEM software. The quenching results after optimization are compared with those before optimization. The comparison shows that the quenching quality after optimization is better than that before optimization. After optimization, the four optimization objectives are all improved.     

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The log-normal distribution is a common choice for modeling positively skewed data arising from many practical applications.This article introduces a new method of constructing confidence interval for a common mean shared by several log-normal populations through confidence distributions, which combines all information from independent sources. We develop a non-trivial weighting approach by taking account of the sample variances of related quantities to enhance efficiency. Combined confidence distributions are used to construct confidence intervals for the common mean and a simplified version of one existing method is also proposed. We conduct simulation studies to evaluate the performance of the proposed methods in comparison with existing methods. Our simulation results show that the weighting approach yields shorter interval length than the non-weighting approach. The newly proposed confidence intervals perform very well in terms of empirical coverage probability and average interval length. Finally, applications of the proposed methodology is illustrated through three real data examples.     

The Relation between Gas Demand and Temperature: A Study in Statistical Demand Forecasting

The paper describes the methods of relating gas demand to temperature which have previously been used for forecasting gas demand in the North Western Area, and introduces a new approach which involves the use of exponential weighting as applied to the average temperatures occurring in the 4 weeks prior to the forecast. An analysis of previous gas demand experience (in relation to actual temperatures throughout) showed that the new method gave a much improved fit to the data, and that this accuracy was maintained even in prolonged periods of abnormal weather conditions. The new method also threw more light on the effect on gas demand of other meteorological factors apart from temperature, and showed up significant effects which had not been detected when using other methods. The method can be used for forecasting on both a daily and a weekly basis, and is considered to represent a significant step forward in the technique of gas demand forecasting.     

Return and Value at Risk using the Dirichlet Process

There exists a wide variety of models for return, and the chosen model determines the tool required to calculate the value at risk (VaR). This paper introduces an alternative methodology to model‐based simulation by using a Monte Carlo simulation of the Dirichlet process. The model is constructed in a Bayesian framework, using properties initially described by Ferguson. A notable advantage of this model is that, on average, the random draws are sampled from a mixed distribution that consists of a prior guess by an expert and the empirical process based on a random sample of historical asset returns. The method is relatively automatic and similar to machine learning tools, e.g. the estimate is updated as new data arrive.