灰色GM(1,1,(√t))模型及在药动学中的应用

将灰色理论用于人体药物代谢动力学的研究,建立了一种新的灰色模型GM(1,1,(√t)),适合于那些单峰形态的原始数据列.并根据抗高血压药复方卡托普利片的血药浓度给出了灰色药物动力模型.结果表明,精度优于传统的一室模型,而且所用参数少,便于计算.灰色理论可用于药物动力学中单峰序列的研究.     

灰色GM[1,1,t~(1/2)]模型及在药动学中的应用

将灰色理论用于人体药物代谢动力学的研究 ,建立了一种新的灰色模型 GM 1 ,1 ,t ,适合于那些单峰形态的原始数据列 .并根据抗高血压药复方卡托普利片的血药浓度给出了灰色药物动力模型 .结果表明 ,精度优于传统的一室模型 ,而且所用参数少 ,便于计算 .灰色理论可用于药物动力学中单峰序列的研究 .     

线性约束下部分线性模型中估计的渐近性质

考虑回归模型yi=x′iβ+ g(ti) + ei, 0 ≤i ≤nr=Rβ其中(xi,ti)是固定非随机设计点列,xi=(xi1,…,xip)′,β=(β1,…,βp)′(p 1) ,g是定义在[0 ,1]上的未知函数,β是未知待估参数,0≤ ti≤1i,ei 是i.i.d随机误差,且Eei=0 ,Ee2i=σ2 <∞.r是一个J维向量,R是一个J* p列满秩矩阵,基于g的估计取一个非参数权估计,本文讨论了在线性约束下β的最小二乘估计的相合性及渐近正态性.     

NA序列的部分和乘积的渐近正态性

设{Xn;n≥1}是一列同分布的NA序列,μ=EX1>0,σ2=VarX1<∞.在适当的条件下证明了∏nk=1Skn!μn1γσndeN,n→∞,其中Sk=∑ki=1Xi,γ=σ/μ,σ2n=Varγ1∑k=n1kSμk-1,N是标准正态随机变量.     

扭曲退化同宿分支

§ 1　 HypothesesConsider the following system:z.=f(z) , (1 .1 )and its perturbed systemz.=f(z) +g(z,μ) (1 .2 )where z∈ Rm+n,μ∈ Rk,k≥ 3,0≤ |μ| 1 ,f,g∈ Cr,r≥ 4 ,g(z,0 ) =0 .For simplicity,we sup-pose thatf(p) =0 ,g(p,μ) =0 .Moreover,for(1 .1 ) we assume(H1 ) The stable manifold Wspand the unstable manifold Wupof z=p are m-dimension-al and n-dimensional,respectively.The linearization Df(p) atthe equilibrium z=p has realmultiple-2 eigenvaluesλ1 and -ρ1 ,such thatany remaining eige…     

THE GEOMETRY OF HYPERSURFACES IN A KAEHLER MANIFOLD

Let M be a complex analytic manifOld there is given a positive definite quadratic differentialform[1]dS2 = gjkdZJdZ* (1)where the Latin indices j, k take the values 1,2,' l n; 1, 2,' t n. Assume the Greek indices o, Ptake the value8 1,2,', n and.=. l cr if i= al = 1 cr if i= a, (2)t cr if i = cr.Assume now that the symmetric tensor gjk is selfadoint(see below Definitioll l), that is-- --gap = g95 = go0 = g9rr, (3)g.0 = gPcr = gap = g05. (4)and 8atisfiesgoP = gap = 0. (5)From the com…     

对加权蛛网模型稳定性的探讨

在传统的蛛网模型中引入权值,用以反映生产者对未来市场的预测和决策,并利用动力系统知识研究了需求函数y=f(x)和供应函数x=g(y)交点(即平衡点)的稳定性条件.当用近两周期价格加权平均预测下一周期商品的价格,从而确定生产数量时,即x_(k+1)=g(λy_k+y_(k-1))/(1+λ)),对任意的λ∈(0,+∞),证明了当λ=2时,平衡点的稳定区域最大(αβ3),其中-α,β分别为需求函数和供应函数在平衡点处的斜率;当用近三个周期价格加权平均预测下一周期商品的价格,从而确定生产数量时,即xk+1=g(λy_k+μy_(k-1)+y_(k-1))/(1+λ+μ),证明了当λ=5,μ=4时,平衡点的稳定区域为αβ5.与传统的蛛网模型相比,平衡点的稳定区域扩大了,从而更有利于经济趋于稳定.     

巧用方差解题

命题　对于ａｉ∈Ｒ (ｉ =1,2 ,… ,ｎ) ,记 ｘ =1ｎ ｎｉ =1ａｉ,ｓ2 =1ｎ ｎｉ =1(ｘｉ- ｘ) 2 =1ｎ ｎｉ=1ｘ2 ｉ- ｘ2 ,则ｓ2≥ 0 (当且仅当ｘ1=ｘ2 =… =ｘｎ= ｘ时取等号 ) .本文举例说明这一命题在解题中的巧用 .1　用于求最值例 1　求函数 μ =2ｘ - 1 5 - 2ｘ的最大值 .解　元素 2ｘ - 1与 5 - 2ｘ的平均数 Ｍ =μ2 ,方差ｓ2 =2ｘ - 12 5 - 2ｘ22 - (μ2 ) 2 =2 -μ24 .由命题知 ,2 - μ24 ≥ 0 (当且仅当 2ｘ - 1=5 - 2ｘ =μ2 时取等号 ) ,所以 0 <μ≤ 2 2 (当且仅当ｘ =32 时取等号 ) ,故当ｘ =32 时 ,μｍａｘ=2 2 …     

数学问题与解答

20 0 3年 1 2月号问题解答(解答由问题提供人给出 )1 466　设M =5 2 0 0 1 + 72 0 0 2 + 92 0 0 3+ 1 1 2 0 0 4 ,求证 :M能被 8整除 .证明　令An =5 2n- 1 ,Bn =72n,Cn =92n- 1 ,Dn =1 1 2n(n∈Z+)( 1 )当n=1时 ,有A1 =5 ,B1 =49,C1 =9,D1 =1 2 1 ,所以A1 除以 8余 5 ;B1 除以 8余 1 ;C1 除以 8余 1 ;D1 除以 8余 1 .( 2 )假定n=k(k∈Z+)时 ,有Ak 除以 8余 5 ,即Ak =5 2k- 1 =8S1 + 5 (S1 ∈Z+) ;Bk=72k除以 8余 1 ,即Bk=72k=8S2 + 1 (S2∈Z+) ;Ck =92k- 1 除以 8余 1 ,即Ck =92k- 1 =8S3+1 (S3∈Z+) ;Dk =1 1 2k 除以 8余 1 …     

污染数据半参数回归模型估计的渐近正态性

考虑半参数回归模型：yi=xiβ g(ti) e1,i=1,2,…,n,其中Ee1=0,Ee^2/1=δ2/1>0．假定y1,y2,…,y0受到另一独立同分布随机变量序列μ1,μ2,…,μn的污染,{μi}与{y1}独立,且仅能观察到污染数据.[ι]对由污染数据作出的参数β的估计βn,证明了它的强相合性．而本则证明了它的渐近正态性．     

渗流问题灰色数值模型的解法研究

灰色数值模型的求解是研究灰色数值模型的一个重要问题 .本文根据灰集合、灰数及其灰色运算规则 ,在渗流系统的基本灰色数值模型的基础上 ,分析了求解这类模型的一整套灰色数值算法 ,并对灰色数值算法、普通算法和经典数值方法的计算结果进行了全面比较 ,论证了灰色数值算法对灰信息传递的正确性和对渗流系统描述的合理性 .     

一类灰色组合投资决策方法

以灰色系统理论和概率论为基础,探讨了含有区间灰数的组合投资决策问题,提出了具有交易费用的灰色组合投资模型的有效解及其临界最优解和均值白化最优解的概念.并且指出了这些概念所对应的投资偏好.利用分析方法和技巧,融合经典组合投资理论,构建了带有交易费用的灰色组合投资模型的熵权分析算法.为不确定型组合投资决策方法的研究提出了一条新思路.文中的算例说明了算法的可行性.     

基于统一灰色生成算子的三参数离散灰色预测模型及其应用

现有三参数离散灰色预测模型的累加阶数取值范围局限于正实数,导致模型建模能力和作用空间受限。为此,论文首先引入实数域统一灰色生成算子;然后,基于统一灰色生成算子构造了新型三参数离散灰色预测模型,实现了其阶数从正实数到全体实数的拓展与优化,从而使得新型模型具备挖掘时序数据积分特性与差异信息的双重功能;最后,将该新模型应用于某装甲装备维修经费的建模,结果显示其精度优于其它同类灰色模型。本研究成果对完善灰色算子基础理论及提高灰色预测模型建模能力具有重要价值。     

加权累加生成的GM(1,1)模型及其应用

根据灰色系统理论中的新信息优先原理知新信息对认知的作用大于老信息的作用,而传统的累加生成没有体现原始数据中新信息的重要性.针对这一问题提出了加权累加生成的概念,并对加权累加生成在单调性、灰指数规律、凸性等方面的性质进行了研究,得到加权累加生成序列具有单调递增性,具有较强的指数规律,并具有下凸性,然后建立了基于加权累加生成的GM(1,1)模型.通过具体算例的计算表明,加权累加生成的GM(1,1)模型的模拟和预测精度比传统的GM(1,1)模型模拟和预测精度高,从而说明了该法的有效性.     

灰色正项几何规划研究

In the model of geometric programming, values of parameters cannot be gotten owing to data fluctuation and incompletion. But reasonable bounds of these parameters can be attained. This is to say, parameters of this model can be regarded as interval grey numbers. When the model contains grey numbers, it is hard for common programming method to solve them. By combining the common programming model with the grey system theory, and using some analysis strategies, a model of grey polynomial geometric programming, a model of θpositioned geometric programming and their quasi-optimum solution or optimum solution are put forward. At the same time, we also developed an algorithm for the problem. This approach brings a new way for the application research of geometric programming. An example at the end of this paper shows the rationality and feasibility of the algorithm.     

基于粒子群算法的变权累加生成的GM(1,1)模型

根据灰色系统的新信息优先原理可知新信息对认知的作用大于旧信息的作用,而传统的累加生成没有体现原始数据中新信息的重要性.针对这一问题引入了变权累加生成的方法,并对变权累加生成在单调性、灰指数规律、凸性等方面的性质进行了研究,得到变权累加生成序列具有单调递增性,具有较强的指数规律,并具有下凸性,这些性质是高精度建模的保证,然后建立了基于变权累加生成的GM(1,1)模型,并运用粒子群算法确定了变权累加生成的权重.通过具体的算例计算表明,变权累加生成的GM(1,1)模型能够提高模型的模拟和预测精度.     

A new-structure grey Verhulst model: Development and performance comparison

The structure defect of the traditional grey Verhulst model is a key factor leading to its unstable performance. A new-structure grey Verhulst model (N_Verhulst) was proposed by introducing a new non-homogeneous exponential function. The N_Verhulst model has a better structure and stronger modeling ability; Meanwhile, it overcomes the shortcomings of the traditional Verhulst model including parameter dislocation and unreasonable selection of initial values. Four typical cases were used to test the performance of N_Verhulst, and the simulation/prediction results of the new model were compared with the traditional Verhulst model and the Pearl model. Results showed that the N_Verhulst model had evidently superior performance to the traditional grey Verhulst model, which confirms that the structure development of the new model is reasonable and effective.     

Forecasting tender price index under incomplete information

Tender price index (TPI) is essential for estimating the likely tender price of a given project. Due to incomplete information on future market conditions, it is difficult to accurately forecast the TPI. Most traditional statistical forecasting models require a certain number of historical data, which may not be completely available in many practical situations. In order to overcome this problem, the grey model is proposed for forecasting TPIs because it only requires a small number of input data. For this study, the data source was based on the TPIs produced by the Government's Architectural Services Department. On the basis of four input data, the grey model forecasted TPIs from 1981Q1 to 2011Q4. The mean absolute percentage errors of forecast TPIs in one quarter and two quarters ahead were 3.62 and 7.04%, respectively. In order to assess the accuracy and reliability of the grey model further, the same research method was used to forecast other three TPIs in Hong Kong. The forecasting results of all four TPIs were found to be very good. It was thus concluded that the grey model could be able to produce accurate TPI forecasts for a one-quarter to two-quarter forecast horizon.     

A new multivariable grey prediction model with structure compatibility

A new multivariable grey prediction model was proposed by adding a dependent variable lag term, a linear correction term and a random disturbance term to the traditional GM(1,N) model. It was theoretically proved that the new model can be completely compatible with the mainstream single variable and multivariable grey prediction models by adjusting and changing the model's parameters. To test the performance of the new model, three case studies were performed. The simulation and prediction results of the new model were compared with those of other grey prediction models. Results showed that the new model had evidently superior performance to other grey models, which confirms that the structure design of the new model is more reasonable than those of the other existing grey prediction models.