协方差改进法及其应用

协方差改进法是构造更好估计的一个有力工具，本文在系统讨论了这个方法及其重要性质基础上，综述了它在许多模型的参数估计中的应用。这包括半相依回归模型，线性回归模型和生长曲线模型。本文还提出了几个未解决的问题。     

协方差矩阵扰动生长曲线模型岭估计的影响分析

本文研究了协方差矩阵发生扰动时，生长曲线模型岭估计的影响分析，建立了生长曲线模型、协方差矩阵扰动生长曲线模型岭估计之间的关系式。讨论了协方差扰动和数据删除对岭估计的影响，导出了度量影响大小的基于岭估计的广义Cook距离Di^*（k）最后，用实例说明了用Di^*(k）度量生长曲线模型的影响点是有效的。     

生猪生产的最优利润

线性规划（ＬＰ）用于确定饲料最低费用配比已有多年的历史。但确定饲料配比仅是农场主所关心的一件事，他们的主要目的是为了从生产中获取最大的利润。本文提出了基于ＬＰ的饲料规划方案，以便使猪是佳地生长，同时也使养猪者获取更大的生产利润。在最大利润模型中，售价和重量的乘积作为收入，饲料费和间接费作为成本。解中包括猪饲料的总量和猪应有的最佳重量。为了把猪的生长模式引入到ＬＰ模型中，我们用数学生长函数来表达生长率和猪龄之间的关系。该函数是经过适当的转化，用回归方法估算出来的。猪在不同生长阶段的营养需求是依据其生长模型和饲料转化率分析的。把上述结果全都引用到ＬＰ模型中，这样可以使利润最优化。实际数据的检验表明：在实践中，ＬＰ模型的结果是合理的。     

生长曲线分析中的多水平模型及算法

生长曲线分析是了解事物随时间的变化特点的分析热点.然而,传统的曲线拟合方法不适用通过重复测量得到的结构资料.采用轮廓设计矩阵运算虽然解决结构资料的生长曲线分析,但是相应的SAS程序冗长且难懂.将多水平模型应用于生长曲线的分析,通过实例分析介绍应用过程,同时给出简单明了的SAS程序.     

外贸出口发展战略模型体系设计

本文结合实际课题的需要，从出口发展研究中几个主要方面内容：出口产业结构优化，出口商品结构优化、出口生产力布局优化，出口发展战略目标等，采用现代化技术手段设计了一个包括１２个子模型的出口发展研究模型体系，运用于实际工作中，效果很好。     

一种肿瘤生长自由边界问题整体解的存在唯一性

研究了一种肿瘤生长模型中自由边界问题，该肿瘤生长模型异于其它此类模型之处就在于采用了新的方式来描述繁衍细胞和休眠细胞的运动．运用抛物型方程的Lp理论和不动点原理，证明了该模型存在唯一的整体解．     

几种结构非概率可靠性模型的比较研究

相对概率可靠性模型和模糊可靠性模型,基于区间分析的结构非概率可靠性模型对数据的要求低,因此在实际工程中对非概率可靠性模型的研究越来越重要.近年来,非概率可靠性理论得到了很好的发展和完善.文中综述了已有的4种主要的非概率可靠性模型,针对线性结构功能函数,分别从度量原理、可靠性指标物理意义、适用范围和结果精度等方面对各可靠性模型进行比较与总结;针对非线性结构功能函数,对各可靠性模型的适用性进行了初步的讨论,从而对非概率可靠性模型有更加全面和深刻的理解,为实际工程中非概率可靠性模型的选取提供重要的理论依据.     

带生长函数的林龄结构植物病虫害模型平衡态的稳定性

本文首先用偏微分方程描述了一类带生长函数的具有林龄结构的植物病虫害模型;其次主要利用算子理论、积分方程理论证明了模型解的存在唯一性,利用对应的特征方程讨论了系统平衡态的稳定性.     

区域发展战略规划群体决策支持系统(Ⅱ)

本文介绍了一个用于区域发展战略规划设计与管理控制支持的群体决策支持系统中的群体决策支持模型部分，内容包括群体支持模型的功能、结构及其相应算法。     

我国出口支柱产业结构优化的非线性目标规划模型及应用

本文建立了我国出口支柱产业结构优化的非线性目标规划控制模型，并介绍了一种解决这个模型的新型算法．它对我国明确出口产业序列和产品序列，优化出口产业结构具有重要的理论和现实意义．     

A generalized Borgonovo's importance measure for fuzzy input uncertainty

In this work, the way in which fuzzy uncertainty in a model's output is apportioned to fuzzy uncertainty in model inputs is studied through a sensitivity analysis. Here, an optimization technique is employed to obtain the membership functions of the fuzzy structural response, for which a global sensitivity indicator is introduced to measure the influence of fuzzy input uncertainty on fuzzy output uncertainty. The global sensitivity indicator is the important measure of the fuzzy input uncertainty, which extends Borgonovo's measure. In this study, the mathematical properties of the important measure of the fuzzy input uncertainty are discussed and proved. The results of numerical examples and engineering examples show that the proposed importance measure can effectively describe the effect of fuzzy input uncertainty on fuzzy structural response. When the sensitivity indicator is larger, the basic fuzzy-valued variable becomes more important. The sensitivity indicators of the fuzzy structural response can give an essential importance sequence of all the basic fuzzy-valued variables and identify key contributing fuzzy-valued variables. The sensitivity indicators can provide the availability guidance to reduce the number of basic variables and optimize the fuzzy response model.     

Study on network traffic forecast model of SVR optimized by GAFSA

There are some problems, such as low precision, on existing network traffic forecast model. In accordance with these problems, this paper proposed the network traffic forecast model of support vector regression (SVR) algorithm optimized by global artificial fish swarm algorithm (GAFSA). GAFSA constitutes an improvement of artificial fish swarm algorithm, which is a swarm intelligence optimization algorithm with a significant effect of optimization. The optimum training parameters used for SVR could be calculated by optimizing chosen parameters, which would make the forecast more accurate. With the optimum training parameters searched by GAFSA algorithm, a model of network traffic forecast, which greatly solved problems of great errors in SVR improved by others intelligent algorithms, could be built with the forecast result approaching stability and the increased forecast precision. The simulation shows that, compared with other models (e.g. GA-SVR, CPSO-SVR), the forecast results of GAFSA-SVR network traffic forecast model is more stable with the precision improved to more than 89%, which plays an important role on instructing network control behavior and analyzing security situation.     

Influence of the nearest-neighbor connections on shaping weighted evolving network

This paper proposes an extended local-world evolving network model consisting of global strength-driven preferential attachment for one central node, and local weight-driven preferential attachment for nearest neighbors of the central node. Analytical predictions and numerical simulations were executed for network evolutions and distributions. The obtained power-law behaviors display the same exponent functions as the ones in a classic model. More comparisons between these two models were made to investigate the structural differences that the nearest-neighbor connections result in. Compared with the counterpart, the proposed model shows a higher clustering coefficient, the varying average shortest path length and the significant hierarchical organization. our model is generally robustness and yet fragility, and is weaker in synchronizability than the counterpart. All those results are added to our understanding of how the rule of the nearest-neighbor connections affects the characteristics of weighted evolving network.     

A conic relaxation model for searching for the global optimum of network data envelopment analysis

Network data envelopment analysis (DEA) models the internal structures of decision-making units (DMUs). Unlike the standard DEA model, multiplier-based network DEA models are often highly non-linear and cannot be converted into linear programs. As such, obtaining a non-linear network DEA's global optimal solution is a challenge because it corresponds to a nonconvex optimization problem. In this paper, we introduce a conic relaxation model that searches for the global optimum to the general multiplier-based network DEA model. We reformulate the general network DEA models and relax the new models into second order cone programming (SOCP) problems. In comparison with linear relaxation models, which is potentially applicable to general network DEA structures, the conic relaxation model guarantees applicability in general network DEA, since McCormick envelopes involved are ensured to be finite. Furthermore, the conic relaxation model avoids unnecessary linear relaxations of some nonlinear constraints. It generates, in a more convenient manner, feasible approximations and tighter upper bounds on the global optimal overall efficiency. Compared with a line-parameter search method that has been applied to solve non-linear network DEA models, the conic relaxation model keeps track of the distances between the optimal overall efficiency and its approximations. As a result, it is able to determine whether a qualified approximation has been achieved or not, with the help of a branch and bound algorithm. Hence, our proposed approach can substantially reduce the computations involved.     

全球化背景下核型创新网络竞争机制研究——基于改进LV-EG模型的仿真分析

在全球化背景下,核型创新网络在向全球创新网络演进的过程中面临多市场竞争和关键资源竞争的双重考验。首先构建全球市场环境下核型创新网络多层次竞合模型;其次,运用Lotka-Volterra模型和演化博弈模型分别剖析核心企业间的竞争关系和尾端企业间的竞合关系,并据此构建改进的LV-EG模型以分析尾端企业竞合关系对核心企业间竞争关系的作用机理;最后,运用matlab对改进的LV-EG模型进行仿真。仿真结果表明:核心企业的尾端企业报酬支付能力、创新产品生产能力、创新环境和网络结构对核型创新网络在全球范围内吸引优质企业并在全球市场环境中获取竞争优势具有重要影响。     

Global and variable cost manufacturing systems

The advent of global manufacturing companies has led to a series of new challenges and problems. One of the more important of these is planning capacity and facilities in the environment of exchange rate uncertainties. While exchange rate uncertainty is a feature of a global environment, the problem formulations actually apply to a wide range of facility and network design problems. This article presents a series of models and results to address these problems.     

Classification of Structural Complexity for Mine Ventilation Networks

The mine ventilation system is most important and technical measure for ensuring safety production in mines. The structural complexity of a mine ventilation network can directly affect the safety and reliability of the underground mining system. Quantitatively justifying the degree of complexity can contribute to providing a deeper understanding of the essential characteristics of a network. However, so far, there is no such a model which is able to simply, practically, reasonably, and quantitatively determine or compare the structural complexity of different ventilation networks. In this article, by analyzing some typical parameters of a mine ventilation network, we conclude that there is a linear functional relationship among five key parameters (number of ventilation network branches, number of nodes, number of independent circuits, number of independent paths, and number of diagonal branches). Correlation analyses for the main parameters of ventilation networks are conducted based on SPSS. Based on these findings, a new evaluation model for the structural complexity of ventilation network (which is represented by C) has been proposed. By combining SPSS classification analyses results with the characteristics of mine ventilation networks, standards for the complexity classification of mine ventilation systems are put forward. Using the developed model, we carried out analyses and comparisons for the structural complexity of ventilation networks for typical mines. Case demonstrations show that the classification results correspond to the actual situations. © 2014 Wiley Periodicals, Inc. Complexity 21: 21–34, 2015     

Modelling enterprise networks: A master equation approach

We are interested in the problem of the mathematical modelling and simulation of groups of small enterprises. This is where a network of small enterprises is established in order to achieve a global objective. Each enterprise contributes to the network but keeps its own individual identity. Apart from having to model economic factors, we have to consider social phenomena and human factors which have an important influence on the dynamical evolution of the network. This paper is devoted to an approach for modelling the dynamical evolution of the social phenomena, based on a master equation approach and introducing non-linear effects.     

A facility location model for global closed-loop supply chain network design

Forward and reverse supply chains form a closed-loop supply chain. In this paper, a mathematical model is proposed for a closed-loop supply chain network by considering global factors, including exchange rates and customs duties. The model is a multi-objective mixed-integer linear programming model under uncertain demand. A solution approach based on fuzzy programming is developed for solving the optimization problem. The model is then applied in a network, which is located in Southwestern Ontario, Canada. A sensitivity analysis is provided to validate the model. This model considers global factors, multi-objectives, and uncertainty simultaneously in a closed-loop supply chain network.