硝苯地平缓释片释放过程的灰色数学模型

采用高分子材料制成硝苯地平缓释片 ,测定其释放度 ,以灰色数学模型进行分析 .结果表明 ,用灰色数学模型对药物释放过程进行拟合 ,拟合精度高 ,结果可靠 .灰色数学模型可用于描述其释药行为 .     

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 .     

基于灰色理论的漂浮性海藻酸钠微球药物缓释模型

以阿维菌素(AVM)为囊芯材料,海藻酸钠(SA)为包埋材料,通过添加发泡剂的形式,在C a2+的交联浴中制备了漂浮性SA微球.通过实验对漂浮性SA微球中AVM的释放情况进行检测,并应用灰色理论的GM(1,1)模型对微球的药物缓释性能进行了模拟和预测,结果显示模型的模拟值和预测值与实验数据的相对误差较小.表明灰色理论模型可用于模拟和预测SA微球的药物释放过程.     

基于灰色马尔科夫模型的陕西省铁路客运量预测

随着我国高铁客运的快速发展,从铁路客运历史趋势中探寻规律、把握铁路客运发展趋势,旨在对中国铁路公司及相关企业的决策提供科学依据.基于2005-2016年陕西省铁路客运量数据,在灰色GM(1,1)模型预测的基础上,运用马尔科夫过程对预测值进行修正,并对2017-2022年陕西省铁路客运量进行预测.结果表明:经过马尔科夫过程修正的灰色预测模型平均绝对误差由原来的4.64%降低到2.94%,预测效果明显.经检验,灰色马尔科夫模型的精度等级为一级,说明了方法对陕西省铁路客运量预测的有效性.     

北京市交通运输、仓储和邮政业增加值的灰色马尔科夫预测模型

将2000-2017年北京市交通运输、仓储和邮政业产值作为原始数据系列,应用灰色模型对时序数据的总体趋势进行拟合,选取相对误差作为随机波动过程,对预测结果进行修正,最后运用灰色马尔科夫模型对未来5年北京市交通运输、仓储和邮政业的产值进行实例预测.结果表明:经过马尔科夫过程修正的灰色预测模型平均预测精度由原来的90.82%提升到97.14%,预测效果明显,说明了方法对北京市交通运输、仓储和邮政业增加值预测的有效性.     

基于灰色马尔科夫模型的平顶山市空气污染物浓度预测

选用平顶山市2005—2009年各空气污染物浓度作为原始数据序列,建立灰色马尔科夫预测模型,对未来10年的污染因子浓度进行预测.模型检验结果表明:均方差比值和小误差概率均为一级;运用灰色关联分析法计算各污染物原始数据序列与预测数据序列之间的关联度,定量描述灰色马尔科夫预测模型对于空气质量预测的精确度,平均精度达到99.9%,表明灰色马尔科夫预测模型对于空气质量预测有很高的实用性.     

基于初值修正的组合灰色Verhulst模型

对灰色Verhulst模型的拟合精度进行了分析,表明初值的选取对模型精度有重要影响.为提高灰色模型的拟合精度,利用最小二乘原理确定初值中的待定常数,给出了初值修正的灰色Verhulst模型.进一步利用修正模型和传统灰色Verhulst模型建立了组合灰色Verhulst模型,在平均相对误差最小的原则下,利用蚁群算法确定组合权系数.最后通过两个应用实例进行了计算和分析,结果表明,通过初值修正和组合模型能够提高灰色Verhulst模型的拟合精度,便于通过程序实现.     

堆浸浸出率灰色动态GDM(1,1)预测研究

基于灰色系统理论扩展了GM(1,1)模型建模方法.给出了一些既改善原始数据列的光滑度,又减少还原误差的变换函数构造条件.首次将灰色动态模型结合变换函数应用于堆浸过程浸出率的预测.结果表明:该方法预测精度高,为实现浸出动力学未来行为的预测和控制提供了一种新的方法.     

分数阶灰色累减生成算子及其性质研究

给出了分数阶灰色累减生成算子的详细推导过程,并证明了分数阶灰色累减生成算子的不动点定理、信息优先原理、交换律与指数律,为分数阶灰色预测模型提供了理论基础.算例验证了分数阶灰色累减生成算子的特征,在灰色预测模型GM(1,1)中的应用证明了分数阶灰色累减生成算子的有效性.     

火灾发生的周期性规律及其在火灾非线性组合预测模型中应用

研究火灾发生规律及发展趋势,具有实用价值.分析历年中国火灾统计数据,发现中国火灾的发生规律同时具有增长趋势性和周期波动性特征:①中国火灾从90年代开始大幅度增加,在2002年达到最大,然后逐年缓慢下降;②每年12个月呈正弦函数波动,周期为12,1、2月发生起数最大,8、9月最小.借助于M ATLAB软件,根据2000-2006年中国火灾统计数据,建立火灾的月发生起数的非线性周期性组合预测模型,预测值与实际值的平均相对误差小于0.07.研究结论为消防研究、消防部门决策提供科学依据.     

控制图的报警系统

控制图中的报警系统是由异常点来启动的，而异常点的判断则取决于小概率事件的发生．本文推导出用容量为。的样本均值■和标准差Ｓｎ来估计总体均值和标准差时、点落在控制界限之外的分布．弥补了直接用总体均值ｕ和标准差σ来计算小概率事件所造成的误差．并由此统一了控制图的报警阀值．     

Order release planning by iterative simulation and linear programming: Theoretical foundation and analysis of its shortcomings

Planning future order releases for complex manufacturing systems with substantial lead times must consider limited capacities and the resulting production smoothing problem as well as the highly nonlinear relationship between capacity utilization, work-in-process and flow times. An important solution approach that has been proposed for this problem is to iterate between an order release model with fixed lead times and a lead time estimation (usually simulation) model that estimates the flow times for given order releases, providing the lead times for the next iteration. However, the convergence of this iterative procedure is highly unpredictable, limiting its practical use.The iterative mechanism is analyzed analytically for simplified formulations of the order release and lead time estimation model. We show that an order release procedure of this type that iterates on the lead times is a dual (price) coordination mechanism whose design does not meet the theoretical requirements, and there is no straightforward way to overcome this. The analysis also provides insights into the results of several numerical studies from the literature and suggests a possible research direction to improve the method.Order release mechanisms of this type are a special case of a broader class of production planning methods that iterate between the production planning and the production scheduling level in order to provide realistic values for lead times and planned capacities. Providing theoretical underpinning for this type of production planning methods is an important research objective, and the paper pursues this direction for the special case of order release.     

Drug Release Kinetics from Biodegradable Polymers via Partial Differential Equations Models

In order to achieve prescribed drug release kinetics some authors have been investigating bi-phasic and possibly multi-phasic releases from blends of biodegradable polymers. Recently, experimental data for the release of paclitaxel have been published by Lao et al. (Lao and Venkatraman in J. Control. Release 130:9–14, 2008; Lao et al. in Eur. J. Pharm. Biopharm. 70:796–803, 2008). In Blanchet et al. (SIAM J. Appl. Math. 71(6):2269–2286, 2011) we validated a two-parameter quadratic ordinary differential equation (ODE) model against their experimental data from three representative neat polymers. In this paper we provide a gradient flow interpretation of the ODE model. A three-dimensional partial differential equation (PDE) model for the drug release in their experimental set up is introduced and its parameters are related to the ones of the ODE model. The gradient flow interpretation is extended to the study of the asymptotic concentrations that are solutions of the PDE model to determine the range of parameters that are suitable to simulate complete or partial drug release.     

利用GM(1,1)模型预测曲线波形

针对给出的函数y=f(x),x∈[a,b],将其值域进行n等分,设yi为其中任一分点,对应x=xi(i=1,2,…,m),用GM(1,1)模型对序列{x1,x2,…,xm}进行预测,得到曲线y=f(x)在下一段时间与直线y=yi的交点位置.当GM(1,1)模型的误差较大时,可利用带有残差修正的GM(1,1)模型进行残差修正,以提高GM(1,1)模型预测值的精确度.     

Dynamic Release Control Policy for the Semiconductor Wafer Fabrication Lines

We propose a policy for controlling the release of raw wafers into semiconductor wafer fabrication lines. The proposed policy exploits up-to-date factory floor information gathered by tracking systems in order to calculate the timing and amount of new releases to minimize mean flow times and mean tardiness while maintaining the maximum output rates of the system. Extensive computer experiments show that the proposed policy results in at least 23.0 and 17.9% improvements on average in mean waiting time and mean tardiness respectively compared to existing release rules.     

Dynamic modeling of copper flash smelting process at a Smelter in China

Due to the highly dynamic characteristic in copper smelting process at a Copper Smelter in China, it is difficult to maintain high performance level control. As a key process indicator to evaluate smelting performance, matte grade is in urgent need of being monitored online. Thus, a real-time dynamic model of predicting matte grade was developed and validated with data collected at an actual plant. Based on desulfurization ratio of copper concentrate, the model couples dynamic mass balances on each species with equilibrium relationships for major component (Cu, Fe, S, SiO₂, et al.) to form a system of differential and algebraic equations. The simulation results illustrate that the maximum relative error and average relative error of matte grade between measured values and predicted value of the model proposed is 3.3%, and the average relative error is 0.54%, which verify the effectiveness of the model developed in providing the guidance for controlling the copper flash smelting process.     

基于风险-均值分析的供应商选择与订单分配集成优化模型与求解

针对不确定环境下具有不同供应合约的供应商选择与订单分配问题,本文构建了基于风险-均值分析的模糊两阶段多周期集成优化模型。与传统的该问题研究并未充分考虑供应商选择与订单分配两阶段决策的交互影响不同,在该模型中,第一阶段供应商选择的评价目标依赖于后期实际运营中的订单分配决策;并考虑未来需求和实际运营成本的不确定性,引入在险价值和期望值两种决策准则对供应商选择方案的绩效进行评价。提出了该模型的分析求解方法,在险价值得以精确评估,期望值被控制在确定的误差范围内,并可以达到足够的精度要求。     

Some properties of a simple moving average when applied to forecasting a time series

Simple (equally weighted) moving averages are frequently used to estimate the current level of a time series, with this value being projected as a forecast for future observations. A key measure of the effectiveness of the method is the sampling error of the estimator, which this paper defines in terms of characteristics of the data. This enables the optimal length of the average for any steady state model to be established and the lead time forecast error derived. A comparison of the performance of a simple moving average (SMA) with an exponentially weighted moving average (EWMA) is made. It is shown that, for a steady state model, the variance of the forecast error is typically less than 3% higher than the appropriate EWMA. This relatively small difference may explain the inconclusive results from the empirical studies about the relative predictive performance of the two methods.     

晶体热膨胀的谐振子数学模型研究及其应用

提出了一个热膨胀的谐振子数学模型,导出了一个新的等压状态方程,据此可在很宽的温度范围内计算物质的热膨胀系数.应用本文模型,不仅能合理解释热膨胀,而且还能定量计算热膨胀.计算结果表明,计算值与实验值一致,平均误差仅0.3%.