机动目标的跟踪与反跟踪的建模研究

以机动目标的跟踪与反跟踪为研究对象,分析了目标的状态方程和量测方程,当存在多个目标时,仍需考虑不同目标之间数据关联问题.首先,考虑了雷达1、雷达2和3量测数据的连接和融合问题,建立了机动目标的状态方程和量测方程模型,运用卡尔曼滤波器算法对目标航迹进行了在线追踪,得到目标跟踪航迹.其次,进行一次指数平滑法的时间序列预测和实时灰色预测,得到了其目标的着落轨迹、着落点坐标和时间.最后建立新的动态多目标优化模型,运用计算机仿真对跟踪与反跟踪的目标航迹进行了模拟.     

组合模型在我国能源需求预测中的应用

文章首先比较了不同的能源需求预测方法的特点,并选择确定性加随机性时间序列组合模型对我国能源需求进行预测,然后详细介绍了建模的过程,并对模型预测精度和参数稳定性作了评价,结果表明本文采用的组合模型是一种比较有效的预测方法,最后用该模型对我国2004~2020能源需求进行了预测。     

基于灰色GM(1.1)模型的预测研究——邯郸市城镇化水平预测

灰色GM(1.1)模型适合少量数据的系统预测.当随时间序列的数据只有少量几个,无法采用统计和其他的预测方法时,它作为一种少数据的系统预测十分有效.将1999-2003年5年中的邯郸的城镇化水平作为灰色预测的原始数据,建立邯郸市城镇化水平灰色预测模型,并采用残差估计进行模型检验.成功地建立了邯郸市城镇化水平灰色预测模型.     

基于稳健回归的电网高峰负荷预测模型应用

在分析高峰负荷特点的基础上,建立了基于稳健回归模型的高峰负荷预测方法。该方法具有较强的稳健性,适应异常情况下的样本数据,能保持较满意预测精度。通过对辽宁省2002年电网负荷数据的预测模拟,验证了本文高峰预测方法的有效性。     

基于预测精度的多目标组合预测优化模型研究

考虑了组合预测精度的数学期望和预测精度的标准差这两个指标 ,建立了多目标规划组合预测最优化模型 ,并给出其数学规划的解法 .最后进行实例分析 ,结果令人满意 .该模型能反映不同时间序列预测方法有效性     

一类基于OWA算子的组合预测模型及其性质

本文引进近年来提出的有序加权平均（OWA）算子，建立新的组合预测模型。首先指出最大绝对误差最小化的组合预测模型是其特例，并给出其线性规划的求解方法；然后对该模型提出非劣性组合预测、预测方法优超，冗余度等新概念；最后探讨了非劣性组合预测以及冗余预测方法的存在性，并给出冗余信息的判定定理。     

具有离散参数齐次随机场的线性预测（X）

研究在3／4平面上观察时存在遗漏观察的预测问题及在1／4平面上观察到要去预测在3／4平面上齐次随机场的值的预测问题，并建立了这两个预测问题之间的一个对应关系及求出了它们的预测值及预测误差。     

货运量预测方法的比较

本在对货运量预测理论和程序描述的基础上，介绍并比较了常用预测方法的优缺点，重点研究了三层BP神经网络的基本原理，构思了BP神经网络中长期货运量预测模型，并进行了预测，最后根据预测结果，分析了其用于预测的优缺点。     

马尔可夫模型的市场预测方法及其应用

本文简述了马尔可夫模型的基本原理，介绍了利用马氏过程的基本特征．即其平稳性和无后效性．对随机现象进行统计预测的方法。本文选取市场为研究对象，根据产品的市场占有率的随机变化过程，建立起市场占有率的马尔可夫预测模型，并进行了实例分析。在模型的实际应用时，要注意系统状态转移的平稳性和进行系统状态划分的有效性。     

提高GM(1，1)模型拟合预测精度的研究

在简单介绍GM(1,1)模型预测过程的基础上,指出了模型在求解微分方程时已知条件选取和背景值构造两方面存在不足,并对此提出了更换已知条件及通过求解最小值获取背景值构造形式的改进措施.通过把这两种措施进行有机结合,形成了一种新的预测程序和方法.并且通过实例分析证明了这种新的程序和方法的确能够提高GM(1,1)模型的拟合预测精度.     

一种求解组合预测模型权重的新方法

在现有文献研究的基础上,对组合预测模型权重的求解方法作了进一步的研究,给出了一种求解组合预测模型权重的新方法.该方法利用最优化理论当中的库恩—塔克条件,将非线性规划模型转化为线性规划模型,从而克服了现有方法在求解组合预测模型权重时不能求得解析解的不足,最后通过示例计算验证了该方法的有效性.     

返航备降航班高风险频发子集搜索模型

返航备降航班是一种保证航空安全的有效措施,但返航备降航班会带来成本损失,所以对返航备降业务规律进行分析,从而重点监控,在确保安全生产的基础上,有效降低返航备降航班的经济损失。我们可以把确定返航备降航班发生的密集时间段描述为一个多属性空间搜索问题,在许多实践领域存在该类问题,比如商业银行对贷款客户的信用评级、绩效考核等。在多属性组成的多维空间中,存在许多正常点和不正常点,通过建立高风险频发子集搜索模型和算法确定不正常点比较密集的多属性范围,使得在该空间范围内不正常点的比例较高并且总的点的数量达到一定的水平。本文以航空公司安全生产为例,其模型结果在实际生产的运用中取得良好效果,在一年内避免30余班次返航备降。     

A class of methods for linear programming

A class of methods is presented for solving standard linear programming problems. Like the simplex method, these methods move from one feasible solution to another at each iteration, improving the objective function as they go. Each such feasible solution is also associated with a basis. However, this feasible solution need not be an extreme point and the basic solution corresponding to the associated basis need not be feasible. Nevertheless, an optimal solution, if one exists, is found in a finite number of iterations (under nondegeneracy). An important example of a method in the class is the reduced gradient method with a slight modification regarding selection of the entering variable.     

Improved pollution forecasting hybrid algorithms based on the ensemble method

In a new fine particle concentrations forecasting model, the Hampel identifier outlier correction preprocessing detects and corrects the outliers in the original series. Empirical wavelet transform method decomposes the corrected series into a set of subseries adaptively, and each subseries are used to train the Stacking ensemble method. In the Stacking ensemble forecasting method, the outlier robust extreme learning machine meta-learner combines different Elman neural network base learners and outputs the forecasting results of different subseries. Different forecasting subseries are combined and then reconstructed by inverse empirical wavelet transform reconstruction method to get the final forecasting fine particle concentrations results. It has been proved in the study that the model proposed in the study has better accuracy and wide applicability comparing to the existing models.     

Stability analysis of the Kaldor model with time delays: monetary policy and government budget constraint

We analyze the model with monetary policy based on the Kaldor's business cycle theory. We introduce the government sector, which conducts the fiscal policy and monetary policy to stabilize the economy. The execution of such a policy needs legislation, and generally, the legislative process is time consuming. We investigate in this paper how the fiscal policy with a time delay affects stability of the economy.We assume that the monetary policy is conducted as a countermeasure of the fiscal deficit by the government, and we consider two extreme cases, namely money finance and bond finance case. In each case, when no time delay exists for the fiscal policy, Keynesian fiscal policy is the preferred method for preventing the economic fluctuations. However, it is not so simple when the time delay exists in the fiscal policy. There exists the policy, which stabilizes the economy under any time delay in the money finance case. On the other hand, in the bond finance case, such a policy does not exist and as the time delay increases the economy becomes unstable. However in both cases, contrary to the expectations of the government, the stronger the fiscal policy, the more unstable the economy becomes for the short time delay.     

一类宏观经济模型的极限特征

利用投入产出分析法建立了一类动态宏观经济模型 ,讨论了在生产增长的条件下 ,当规划期足够长时 ,有消费的经济系统中 ,投入、产出和消费之间的关系及其极限特征 .说明了 :系统的初始投入不一定是直接消耗系数矩阵的正特征矢量 .并且 ,在经济不出现危机的条件下 ,系统以稳定状态增长 ,呈现大道性质 .     

模糊环境下消费类电子产品推荐方法研究

基于消费类电子产品自身的特点,提出一种新型的推荐方法。首先,考虑专家对备选产品进行评分时存在信息共享性,提出处理专家之间相互关联的直觉梯形模糊Shapley加权几何算子,并研究该算子的相关性质。其次,针对专家权重信息部分已知情况,建立规划模型求解专家的Shapley权重值,并运用所提算子对专家意见进行集成以得到各标准下各备选产品的综合评分。在给定顾客目标需求的基础上,基于投影法求出各备选产品在目标产品上的投影值,并将投影值最大的产品推荐给顾客以完成推荐过程。最后,以戴尔中国官网上的笔记本电脑购买为例,阐述该推荐方法的可行性和实用性。     

An iterative back substitution algorithm for the solution of tridiagonal matrix systems with fringes

For tridiagonal matrix systems, a simple direct algorithm giving the solution exists, but in the most general case of tridiagonal matrix with fringes, the direct solving algorithms are more complicated. For big systems, direct methods are not well fitted and iterative algorithms are preferable. In this paper a relaxation type iterative algorithm is presented. It is an extension of the backward substitution method used for simple tridiagonal matrix systems. The performances show that this algorithm is a good compromise between a direct method and other iterative methods as block SOR. Its nature suggests its use as inner solver in the solution of problems derived by application of a decomposition domain method. A special emphasis is done on the programming aspect. The solving Fortran subroutines implementing the algorithm have been generated automatically from their specification by using a computer algebra system technique.     

Forecasting model with asymmetric market response and its application to pricing of consumer package goods

This paper presents a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by threshold models. As a threshold variable to generate a mechanism for different market responses, we use the counterpart to the concept of a price threshold applied to a representative consumer in a store. A Bayesian approach is taken for statistical modelling because of advantages that it offers over estimation and forecasting. The proposed model incorporates the lagged effects of a price variable. Thereby, myriad pricing strategies can be implemented in the time horizon. Their effectiveness can be evaluated using the predictive density. We intend to improve the forecasting performance over conventional linear time series models. Furthermore, we discuss efficient dynamic pricing in a store using strategic simulations under some scenarios suggested by an estimated structure of the models. Empirical studies illustrate the superior forecasting performance of our model against conventional linear models in terms of the root mean square error of the forecasts. Useful information for dynamic pricing is derived from its structural parameter estimates. This paper develops a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by the threshold models. Copyright © 2005 John Wiley & Sons, Ltd.