Optimal design accounting for uncertainty in loading amplitudes: A numerical investigation

A numerical investigation is performed addressing the optimal design of stiff structures accounting for uncertainty in loading amplitudes. A minimum volume problem is endowed with a stochastic compliance constraint handling normal distributions and solved adopting mathematical programming. The formulation, originally conceived for a single load case, is extended to handle multiple load cases. Numerical simulations are performed to test the proposed algorithms, pointing out features of the numerical procedures and peculiarities of the stochastic-based optimal solutions achieved for different values of the second-order moments. Comparisons with respect to conventional deterministic layouts are provided as well.     

Robust stability analysis of static neural network with S-type distributed delays

In this paper, we investigate local robust stability of static neural network (SNN) with S-type distributed delays. We derive some new sufficient conditions for local robust stability of equilibrium points and estimate attracting domains of equilibrium points except isolated equilibrium points. Our results not only show local robust stability of equilibrium points but also allow much broader application for static neural network with or without delays. It is shown that our results are new and improve corresponding results existing in the previous literature.     

The Arrow paradox with fuzzy preferences

This note considers a new factorization of a fuzzy weak binary preference relation into its asymmetric and symmetric parts. Arrow’s General Possibility Theorem is then examined within the resulting framework of vague individual and social preferences. The outcome of this exercise is compared with some earlier results available in the literature on the Arrow paradox with fuzzy preferences.     

Modified criteria for global robust stability of interval delayed neural networks

Two simple criteria for global robust stability of Hopfield-type interval neural networks with delay are presented. The criteria turn out to be modified versions of an earlier criterion due to Cao, Huang, and Qu. Examples show the effectiveness of the modified criteria. Numerical simulations are carried out to confirm the applicability of the modified criteria.     

收益管理中单产品动态定价的稳健模型研究

在收益管理的动态定价模型的研究中,由传统的确定性模型和随机模型所得到的定价策略常常受限制于需求估计的准确性,当对需求的估计出现偏差时定价策略可能达不到最大化收益的目的,因此定价策略即最优解的稳健性越来越受到研究者的重视。针对需求函数系数的不确定性,在未知需求分布的条件下,应用稳健最优化思想,提出了一种稳健的动态定价模型,并对模型的最优解和最大收益进行了数值模拟分析。     

Effciency comparison between mean and log-rank tests for recurrent event time data

Recurrent event time data are common in biomedical follow-up studies, in which a study subject may experience repeated occurrences of an event of interest. In this paper, we evaluate two popular nonparametric tests for recurrent event time data in terms of their relative effciency. One is the log-rank test for classical survival data and the other a more recently developed nonparametric test based on comparing mean recurrent rates. We show analytically that, somewhat surprisingly, the log-rank test that onl...     

基于鲁棒性优化的桁架结构失效-安全设计

基于鲁棒优化思想, 提出了桁架结构失效-安全优化设计问题的双层规划算法. 其中上层规划用来寻找杆件的最优尺寸, 而下层规划的目标是确定结构最不利的失效模式. 为了获得下层优化的全局最优解, 以保证所得到的最优结构真正安全可靠, 特别地还发展了相关问题求解的混合0-1规划算法. 与以往研究工作相比, 该方法不需要预先假定破坏模式, 因此更容易获得理论上最优的结果. 数值算例表明了所提出方法的有效性.      

基于几何矩预分类的无人机遥感图像自动配准方法

图像配准技术是近些年来图像处理领域发展迅速的研究方向之一.在遥感领域内,图像配准更是实现图像融合、运动检测、图像校正、图像拼接等应用的一个关键步骤.尽管国内外目前在图像配准方面提出了很多方法,但不同方法适用的图像范围不同,很多时候需要人工干预进行方法的选择.尤其对于无人机这种快速、实时获取图像的新型遥感平台,如何集合不同方法的优点以实现图像自动配准成为了关键性问题.本文在比较分析了基于SIFT和SURF特征提取图像配准方法的各自优势后,提出基于几何矩的方法对图像进行预先分类,从而决定将其分配给何种方法进行配准,实现全程自动化.实验证明,这种图像自动配准方法在拓宽了图像应用范围的同时保证了良好的配准效果.     

A Study of Two-Dimensional Plane Elasticity Finite Elements for Optimal Design

ABSTRACT

Design of structures using a variety of two-dimensional finite elements is considered in this paper. An efficient technique of computing first-order derivatives of pointwise stress constraints for simple and higher-order two-dimensional (membrane) finite elements is presented. Computational aspects of design sensitivity vector calculation, using a semi-analytical method versus traditional methods are presented. Implementation of a fully-stressed design approach to find a suitable initial estimate leads to increased computational efficiency. These aspects of the design procedure are illustrated through analysis of numerical examples. Experience indicates that a suitable mix of low and higher-order elements yields the most efficient and accurate design model.     

混合多属性决策问题中的权重研究

针对属性值以精确数、区间数、直觉梯形模糊数给出的混合多属性决策问题,提出一种基于属性的可靠性、属性对决策的影响度和决策者对属性的重视程度这三个维度给权重赋值的方法。首先对属性的可靠性进行定义,并计算出属性的可靠性;接着根据属性内部差异最大化求出属性对决策的影响度;随后利用直觉梯形模糊数之间的距离求出决策者对属性的重视程度,并用投影模型将这三个维度进行集成,得到最终的权重值。该方法能够使权重的获取更加全面,最后利用算例证明了本文方法的可行性。