A new voltage control equipment using fuzzy inference

Power system control equipment needs higher sensitivity and operational reliability. Advanced voltage control equipment is needed for reducing the frequency of tap changes and improving the characteristics (the relationship between the actual voltage and reference voltage) of the voltage to meet today's power system requirements. However, these objectives are in a trade-off relationship. Studies of voltage control derived from a knowledge base suitable for electric power systems can satisfy these objectives using fuzzy inference. Compared with corresponding conventional equipment, the new equipment improved the deviation of 30 min average voltage of 30 percent. This paper describes the design concept of new voltage control equipment using fuzzy inference. In addition, field test results are described along with rules of fuzzy inference, membership functions, and the deviation of 30 min average voltage through detailed simulation.     

A weighted multivariate Fuzzy C-Means method in interval-valued scientific production data

Clustering is the process of organizing objects into groups whose members are similar in some way. Most of the clustering methods involve numeric data only. However, this representation may not be adequate to model complex information which may be: histogram, distributions, intervals. To deal with these types of data, Symbolic Data Analysis (SDA) was developed. In multivariate data analysis, it is common some variables be more or less relevant than others and less relevant variables can mask the cluster structure. This work proposes a clustering method based on fuzzy approach that produces weighted multivariate memberships for interval-valued data. These memberships can change at each iteration of the algorithm and they are different from one variable to another and from one cluster to another. Furthermore, there is a different relevance weight associated to each variable that may also be different from one cluster to another. The advantage of this method is that it is robust to ambiguous cluster membership assignment since weights represent how important the different variables are to the clusters. Experiments are performed with synthetic data sets to compare the performance of the proposed method against other methods already established by the clustering literature. Also, an application with interval-valued scientific production data is presented in this work. Clustering quality results have shown that the proposed method offers higher accuracy when variables have different variabilities.     

当前我国在学位价值取向上的错位现象及其原因透视

学位具有学术价值、教育价值、管理价值等本体性价值，也具有个体价值与社会价值、工具性价值和目的性价值等派生性价值。当前人们在学位价值取向上存在着一些明显的错位和偏差。其具体表现有四点：一是重学位的“派生”性价值，轻学位的“本体”性价值；二是过分强调学位的教育价值和管理价值，而缺乏对学术价值应有地位的肯定；三是重学位的社会价值，轻学位的个体价值；四是重学位的工具性价值而忽视学位的目的性价值。导致这种错位现象产生的原因，不仅有教育系统内部因素，而且也与中国传统文化价值观和当前社会对人才的选拔、聘用政策有着直接的关系。     

Limit load and shakedown analysis of plastic structures under stochastic uncertainty

Problems from plastic analysis are based on the convex, linear or linearised yield/strength condition and the linear equilibrium equation for the stress (state) vector. In practice one has to take into account stochastic variations of several model parameters. Hence, in order to get robust maximum load factors, the structural analysis problem with random parameters must be replaced by an appropriate deterministic substitute problem. A direct approach is proposed based on the primary costs for missing carrying capacity and the recourse costs (e.g. costs for repair, compensation for weakness within the structure, damage, failure, etc.). Based on the mechanical survival conditions of plasticity theory, a quadratic error/loss criterion is developed. The minimum recourse costs can be determined then by solving an optimisation problem having a quadratic objective function and linear constraints. For each vector a(·) of model parameters and each design vector x, one obtains then an explicit representation of the “best” internal load distribution F^∗. Moreover, also the expected recourse costs can be determined explicitly. Consequently, an explicit stochastic nonlinear program results for finding a robust maximal load factor μ^∗. The analytical properties and possible solution procedures are discussed.     

基于模糊理论的SAR图像分割算法研究与实现

SAR图像存在强烈的相干斑噪声,传统方法不能很好对其分割。文章基于模糊理论,通过选择图像特征,构造模糊集,借助最大隶属度原则进行了SAR图像分割算法的设计,并借助SAR图像分别进行了参数调节和窗口选择的实验,获得了满意的分割结果。实验结果表明,该算法对于SAR图像分割可行有效。     

模糊综合评价法在长江下游贵池河段水质评价中的应用

对水质评价存在诸多方法,而模糊综合评价法具有评价结果合理、更接近客观实际等优点,因而得到越来越广泛的应用。通过模糊评价方法对长江下游贵池河段2005～2009年间水环境综合评价,并采用加权平均原则求取隶属等级,取得较好的效果。     

用高新技术改造传统产业

研究鞍山钢铁集团公司(以下简称鞍钢)的基本状况，并对改造前和改造后的鞍钢状况做了对比分析，明确鞍钢改革的方向。论证了鞍钢用高新技术改造传统产业的策略，指出鞍钢要生存和发展，必须走体制创新、技术创新和管理创新的道路，实现企业结构优化，增强与国际钢铁企业竞争的实力，从而为大型国有企业走出困境提供了一些有益的经验。     

不完备信息系统中一个变精度粗糙集模型

针对不完备信息系统的知识获取,提出了一种基于相容度的变精度粗糙集模型,该模型是变精度粗糙集模型在不完备信息系统中的拓展.定义了这种模型上的知识约简,并给出了求约简的一个启发式算法.最后通过实例分析说明了算法的有效性.     

混合摩擦滑动轴承的模糊可靠性设计

本文应用模糊数学原理研究了混合摩擦滑动轴承的模糊可靠性设计计算方法,导出了相应的计算公式,并给出了应用实例。