Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer

This study applies fuzzy sets to integrate the supply chain network of an edible vegetable oils manufacturer. The proposed fuzzy multi-objective linear programming model attempts to simultaneously minimize the total transportation costs. The first part of the total transportation costs is between suppliers and silos; and rest one is between manufacturer and warehouses. The approach incorporates all operating realities and actual flow patterns at production/distribution network with reference to demands of warehouses, capacities of tin and pet packaging lines. The model has been formulated as a multi objective linear programming model where data are modeled by triangular fuzzy numbers. Finally, the developed fuzzy model is applied for the case study, compiled the results and discussed.     

(L,M)-模糊拓扑空间中模糊紧性的测度

本文借助不等式,在(L,M)-拓扑空间中引入了模糊紧性度的概念,并讨论了它的性质.     

神经元的形态分类和识别——2010年全国研究生数学建模竞赛C题论文

根据神经元的空间几何特征参数,研究神经元的空间形态分类方法,将神经元根据几何形态分类识别.首次提出利用模糊C均值算法(FCM)建立了模糊聚类分析模型,对所给的神经元样本进行了分类,这一模型用来对神经元进行分类比较合理,且计算结果准确.同时,还利用相关分析原理分析了不同动物神经系统中同一类神经元的形态特征有着很高的相似度.     

编序式问卷调查的模糊偏序排序法

讨论了现有的编序式问卷调查排序方法的不足之处;提出了基于模糊偏序关系的编序式问卷调查的排序方法,给出了模糊偏序排序法的数学模型,论证了用模糊偏序关系对编序式问卷调查进行排序是一种较好的方法;并用实例分析了模糊偏序排序法应用于编序式问卷调查的具体操作步骤.     

基于模糊聚类分析的小波神经网络模型在径流预测中的应用

提出了一种在对预报因子集进行模糊聚类分析基础上构建径流预测模型的新方法:先通过模糊C-均值聚类将历史径流数据进行分类,然后利用小波神经网络分别建立预报因子集类别变量特征值与观测值之间的局部预测模型,并设计了特征值分类识别器,自动搜寻相适应的局部网络模型进行预测.通过西南某水库2011年日平均入库来流的计算实例对简单小波神经网络预测模型和所建的基于FCM与小波神经网络的预测模型进行了比较,结果较为满意.     

带未知扰动的多涡卷混沌系统修正函数时滞投影同步

研究了带有未知外部扰动的不同多涡卷混沌系统修正函数时滞投影同步问题. 基于Lyapunov稳定性理论, 采用模糊自适应控制的方法设计自适应同步控制器及参数的更新规则. 该控制器在实现混沌系统修正函数时滞投影同步的同时对外界扰动的变化能保持较好的稳定性. 数值仿真的结果进一步验证了该方法的有效性.     

一款宽光谱鱼眼镜头的设计

讨论了一款用于监控侦查的鱼眼镜头设计.首先根据使用要求,选择了可以由图像直接提取出目标方位信息的等距离投影方式;又由系统对目标分辨率的要求,选择了焦距相对较长的全帧成像形式.通过合理布局系统结构及材料选择,使各种像差得到较好的校正,并通过加大光阑慧差改善系统照度均匀性.最终设计出工作波段486～900nm,视场180°,F/2.8的宽光谱鱼眼镜头,设计结果系统全视场在乃奎斯特频率63lp/mm处的调制传递函数大于0.3,边缘视场照度大于中心视场照度的50%,f-θ畸变小于3%,各项指标满足系统要求.     

The magnet design for the HLS storage ring upgrade project

In order to improve the performance of the Hefei Light Source (HLS), in particular to get higher brilliance synchrotron radiation and increase the number of straight section insertion devices, an upgrade project called HLSII will be launched soon. The storage ring lattice, which has a double bend achromatic structure with four periods, comprises eight dipoles, 32 quadrupoles and 32 combined function sextupoles. The design and analysis of the magnets are shown in this paper, along with the optimization of the multipurpose combined function magnet, which consists of three magnets: skew quadrupole, horizontal dipole and vertical dipole, with the main sextupole magnet. This type of magnet is the first one that has been designed and used in China. The mechanical design and fabrication procedures for the magnets are also presented.     

Tripled coincidence theorems for contractive type mappings in partially ordered metric spaces

In this paper we introduce the concept of a tripled coincidence point for a pair of nonlinear contractive mappings F : X³ → X and g : X → X. The obtained results extend recent coincidence theorems due to ?iri? and Lakshmikantham [V. Lakshmikantham, L. ?iri?, L., Coupled fixed point theorems for nonlinear contractions in partially ordered metric spaces, Nonlinear Anal. 70 (2009) 4341-4349].     

Mining axiomatic fuzzy set association rules for classification problems

In this paper, we propose a novel method to mine association rules for classification problems namely AFSRC (AFS association rules for classification) realized in the framework of the axiomatic fuzzy set (AFS) theory. This model provides a simple and efficient rule generation mechanism. It can also retain meaningful rules for imbalanced classes by fuzzifying the concept of the class support of a rule. In addition, AFSRC can handle different data types occurring simultaneously. Furthermore, the new model can produce membership functions automatically by processing available data. An extensive suite of experiments are reported which offer a comprehensive comparison of the performance of the method with the performance of some other methods available in the literature. The experimental result shows that AFSRC outperforms most of other methods when being quantified in terms of accuracy and interpretability. AFSRC forms a classifier with high accuracy and more interpretable rule base of smaller size while retaining a sound balance between these two characteristics.