基于2-可加模糊测度的NPD项目复杂性评价

针对NPD项目复杂性各因素间具有的关联性以及传统评价方法的局限性,提出一种基于关联多属性的2-可加模糊测度方法来对NPD项目复杂性进行评价。在界定项目复杂性内涵的基础上,从产品复杂性、环境复杂性、组织复杂性和技术复杂性四个方面构建了NPD项目复杂性评价指标体系。从模糊测度、默比乌斯变换和交互作用系数间的转化关系出发,基于最大Marichal熵原则,提出了一种确定2-可加模糊测度值的新方法。利用Choquet积分作为集结算子,自下而上计算各候选方案的综合评价值。最后,通过具体算例说明了该方法的可行性和有效性。     

基于多指标区间逼近的住宅建筑节能改造方案评价

鉴于住宅建筑节能改造的效果的总体评价的复杂性及其影响因素的不确定性,将区间数关联决策方法应用于节能改造效果的评价领域.通过引入区间数序列的范数完成多指标决策矩阵的规范化处理,建立多指标区间数整体逼近关联决策模型,完成住宅建筑节能效果评估得出最终结论.计算实例验证了该模型的有效性和实用性,较好地解决了住宅建筑节能改造效果评价的实际问题,取得较为满意的结果.     

Efficient strategies for deriving the subset VAR models

Algorithms for computing the subset Vector Autoregressive (VAR) models are proposed. These algorithms can be used to choose a subset of the most statistically-significant variables of a VAR model. In such cases, the selection criteria are based on the residual sum of squares or the estimated residual covariance matrix. The VAR model with zero coefficient restrictions is formulated as a Seemingly Unrelated Regressions (SUR) model. Furthermore, the SUR model is transformed into one of smaller size, where the exogenous matrices comprise columns of a triangular matrix. Efficient algorithms which exploit the common columns of the exogenous matrices, sparse structure of the variance-covariance of the disturbances and special properties of the SUR models are investigated. The main computational tool of the selection strategies is the generalized QR decomposition and its modification. This work is in part supported by the Swiss National Foundation for Research Grants 101312-100757/1, 200020-10016/1 and 101412-105978. Correspondence to: Cristian Gatu, Institut d'informatique, Université de Neuchatel, Emile-Argand 11, Case Postale 2, CH-2007 Neuchatel, Switzerland. e-mail: erricos@ucy.ac.cy     

三维坐标转换的两种方法及其比较研究

针对7参数法三维坐标转换问题,对比分析了传统的基于泰勒级数展开的线性模型转换方法和基于罗德里格矩阵的三维坐标转换方法.由于在基于罗德里格矩阵的转换方法中,不需进行三角函数的计算,也不需迭代计算,因而其计算速度更快;而且其解决了线性模型对旋转角大小的限制,不仅适用于小角度的空间直角坐标转换,也能用于大角度的空间坐标转换.实验结果也表明基于罗德里格矩阵的转换方法具有更好的适用性和更高的精度.     

Limiting spectral distribution of large-dimensional sample covariance matrices generated by VARMA

The existence of a limiting spectral distribution (LSD) for a large-dimensional sample covariance matrix generated by the vector autoregressive moving average (VARMA) model is established. In particular, we obtain explicit forms of the LSDs for random matrices generated by a first-order vector autoregressive (VAR(1)) model and a first-order vector moving average (VMA(1)) model, as well as random coefficients for VAR(1) and VMA(1). The parameters for these explicit forms are also estimated. Finally, simulations demonstrate that the results are effective.     

多元FFT与FST的直接方法

一、多元变换矩阵与矩阵的张量积 矩阵的张量积(Kronecker乘积)是导出多元直接变换的主要工具,因此,这里首先列出张量积的定义及其简单性质. 定义.设A_n,B_m分别是n×n,m×m方阵,则A_n与B_m的张量积是一个(n·m)×(n·m)方阵:A_nB_m=[A_nb_(ij)],其中B_m=[b_(ij)].并记A~(k)=?.     

Necessary condition for the existence of the S matrix outside the scope of perturbation theory

Using the Maslov—Shvedov complex-germ method due to Maslov—Shvedov, we obtain a necessary condition for the existence of the quantum-field S matrix outside the scope of perturbation theory in the leading order of semiclassical approximation. This condition consists in that the tangent symplectic transformation to the evolution operator of the nonlinear classical field equation is realized by a unitary transformation of Fock space. It follows from the results of the book of Maslov and Shvedov that this condition always holds.     

A representation model for the solving-time distribution of a set of design tasks in new product development (NPD)

Given the potential risks of new product development projects (NPD), the characteristics of the design tasks solving-time distributions are critical for their effective management. In OR we need to find what operational characteristics of design tasks may delay projects. Other researchers already identified the technological novelty, the magnitude of the design tasks, the interactions between design tasks in an NPD project, and the balancing between projects among the most important causes of the unpredictability of the design tasks lead times in NPD projects.     

岩石裂隙网络的分形特征

分形特征与分形维数广泛应用于岩石裂隙网络的量化,及与工程参数的关系模型建立.然而,严格的分形维数的极限定义形式难以直接应用,工程应用中多用近似分形维数值代替,近似的结果在建立量化关系模型时会产生蝴蝶效应,在量化及预测过程中产生巨大偏差.本文回顾了分形研究一系列的发展过程,并基于最新的分形定义提出了一种新的分形维数计算方法.通过对于十个岩石裂隙网络分形维数的计算,证明该方法能够准确有效的计算出图形的复杂度,避免了以往计算分形维数所产生的问题.     

Dependence Assessment Based on Generalized Relative Complexity: Application to Sampling Network Design

Generalized statistical complexity measures provide a means to jointly quantify inner information and relative structural richness of a system described in terms of a probability model. As a natural divergence-based extension in this context, generalized relative complexity measures have been proposed for the local comparison of two given probability distributions. In this paper, the behavior of generalized relative complexity measures is studied for assessment of structural dependence in a random vector leading to a concept of ‘generalized mutual complexity’. A related optimality criterion for sampling network design, which provides an alternative to mutual information based methods in the complexity context, is formulated. Aspects related to practical implementation, and conceptual issues regarding the meaning and potential use of this approach, are discussed. Numerical examples are used for illustration.     

具有饱和治疗的离散SEIS结核病模型的动力学性态

研究了一类具有饱和治疗的离散SEIS传染病模型的动力学性态.利用再生矩阵的方法定义了模型的基本再生数,直接计算得到了无病平衡点和地方病平衡点的存在性;利用线性化矩阵和Jury判据讨论了平衡点的稳定性;并讨论了模型可能发生的后向分支现象,也通过数值模拟展示了模型的动力学性态.     

Risk-control approach for bottleneck transportation problem with randomness and fuzziness

Solving transportation problems is essential in engineering and supply chain management, where profitability depends on optimal traffic flow. This study proposes risk-control approaches for two bottleneck transportation problems with random variables and preference levels to objective functions with risk parameters. Each proposed model is formulated as a multiobjective programming problem using robust-based optimization derived from stochastic chance constraints. Since it is impossible to obtain a transportation pattern that optimizes all objective functions, our proposed models are numerically solved by introducing an aggregation function for the multiobjective problem. An exact algorithm that performs deterministic equivalent transformations and introduces auxiliary problems is also developed.     

GF（3）上多元多项式的化简

本文通过极性矩阵的递归表示，对ＧＦ（３）上多元多项式环进行了讨论，提出将变量经过线性变换，使多元多项式化简为乘积项数最少的新方法．该方法不需要进行矩阵运算，简便易行，并减少了计算复杂性，其结果改进了［１，２］的工作．     

关键线路变迁分析方法及其应用

传统的关键路线法(CPM),计算工序的诸多时间参数来确定工期与关键路线,对于简单网络方便可行.但对于大型的复杂网络,必然存在时间参数多、计算量大等问题;加之,工程项目具有普遍的复杂性,时常需要进行工期优化,关键线路可能发生变迁.为了简化计算,运用0-1规划方法,在WinQSB环境下建立适应不同规模的网络计划参数计算的数学模型并快速求解,再通过目标函数的灵敏度分析,确定变量的变化范围,解决关键线路变迁问题.算例表明,提出的方法无需重新计算便可快捷地断定关键线路是否发生变迁.     

Subset selection for vector autoregressive processes via adaptive Lasso

Subset selection is a critical component of vector autoregressive (VAR) modeling. This paper proposes simple and hybrid subset selection procedures for VAR models via the adaptive Lasso. By a proper choice of tuning parameters, one can identify the correct subset and obtain the asymptotic normality of the nonzero parameters with probability tending to one. Simulation results show that for small samples, a particular hybrid procedure has the best performance in terms of prediction mean squared errors, estimation errors and subset selection accuracy under various settings. The proposed method is also applied to modeling the IS-LM data for illustration.     

Discussions on non-probabilistic convex modelling for uncertain problems

Non-probabilistic convex model utilizes a convex set to quantify the uncertainty domain of uncertain-but-bounded parameters, which is very effective for structural uncertainty analysis with limited or poor-quality experimental data. To overcome the complexity and diversity of the formulations of current convex models, in this paper, a unified framework for construction of the non-probabilistic convex models is proposed. By introducing the correlation analysis technique, the mathematical expression of a convex model can be conveniently formulated once the correlation matrix of the uncertain parameters is created. More importantly, from the theoretic analysis level, an evaluation criterion for convex modelling methods is proposed, which can be regarded as a test standard for validity verification of subsequent newly proposed convex modelling methods. And from the practical application level, two model assessment indexes are proposed, by which the adaptabilities of different convex models to a specific uncertain problem with given experimental samples can be estimated. Four numerical examples are investigated to demonstrate the effectiveness of the present study.     

一类多时滞中立型广义系统的稳定性判据

研究了多时滞的中立型广义时滞系统时滞相关的渐近稳定性问题,利用Lyapunov-Krasovskii泛函,等价模型转换方法和自由由权矩阵的方法,给出了系统时滞相关渐近稳定的充分条件,所给的判据是线性矩阵不等式形式,可方便运用Matlab工具箱求解,最后用一实例验证了方法的有效性。     

基于复杂性和成本的NPD项目权变管理策略研究

本文在项目管理的选择法和学习法的组合模式的基础上,提出同时采用多方案并行和强化学习两种管理策略能有效应对NPD项目的复杂性。在如何决定并行数量和学习强度的问题上,基于效率准则进行了理论分析,提出了主要的权变变量,即复杂性和成本。并基于NK模型进行了仿真模拟,探讨了不同情境下,项目绩效随两种管理策略的变化规律。     

Effort estimates through project complexity

This paper reports the results obtained from use of project complexity parameters in modeling effort estimates. It highlights the attention that complexity has recently received in the project management area. After considering that traditional knowledge has consistently proved to be prone to failure when put into practice on actual projects, the paper endorses the belief that there is a need for more open-minded and novel approaches to project management. With a view to providing some insight into the opportunities that integrate complexity concepts into model building offers, we extend the work previously undertaken on the complexity dimension in project management. We do so analyzing the results obtained with classical linear models and artificial neural networks when complexity is considered as another managerial parameter. For that purpose, we have used the International Software Benchmarking Standards Group data set. The results obtained proved the benefits of integrating the complexity of the projects at hand into the models. They also addressed the need of a complex system, such as artificial neural networks, to capture the fine nuances of the complex systems to be modeled, the projects.     

Modeling mortality with a Bayesian vector autoregression

Parametric mortality models capture the cross section of mortality rates. These models fit the older ages better, because of the more complex cross section of mortality at younger and middle ages. Dynamic parametric mortality models fit a time series to the parameters, such as a Vector-auto-regression (VAR), in order to capture trends and uncertainty in mortality improvements. We consider the full age range using the Heligman and Pollard (1980) model, a cross-sectional mortality model with parameters that capture specific features of different age ranges. We make the Heligman–Pollard model dynamic using a Bayesian Vector Autoregressive (BVAR) model for the parameters and compare with more commonly used VAR models. We fit the models using Australian data, a country with similar mortality experience to many developed countries. We show how the Bayesian Vector Autoregressive (BVAR) models improve forecast accuracy compared to VAR models and quantify parameter risk which is shown to be significant.