基于深度学习的ELM实时识别研究

基于深度学习的方法，在HL-2A装置上开发出了一套边缘局域模(ELM)实时识别算法。算法使用5200次放电数据(约24.19万数据切片)进行学习，得到一个深度为22层的卷积神经网络。为衡量算法的识别能力，识别了HL-2A装置自2009年实现稳定ELMy H模放电以来所有历史数据(约26000次放电数据)，共识别出1665次H模放电，其中误识别35次，误报率为2.10%。在实际的1634次H模放电中，漏识别4次，漏识别率为0.24%。该误报率和漏报率可以满足ELM实时识别的精度要求。识别算法在实时控制环境下，对单个时间点的平均计算时间为0.46ms，可以满足实时控制的计算速度要求。     

Real time estimation of CO2 laser weld quality for automotive industry

Laser welding is one of the most precise welding processes in joining sheet metals. In laser welding, performing real time evaluation of the welding quality is very important to enhance the efficiency of the welding process. In this study, the plasma and spatter, which are generated during laser welding, are measured using UV and IR photodiodes. The factors that influence weld quality are classified into five categories; optimal heat input, slightly low heat input, low heat input, partial joining due to gap mismatch, and nozzle deviation. The data number deviated from reference signals and their standard deviations were also considered to evaluate the qualities. A system was also formulated to perform real time evaluations of the weld quality using a fuzzy multi-feature pattern recognition with the measured signals.     

模糊线性回归模型的约束最小二乘估计

自Tanaka等1982年提出模糊回归概念以来,该问题已得到广泛的研究。作为主要估计方法之一的模糊最小二乘估计以其与统计最小二乘估计的密切联系更受到人们的重视。本文依据适当定义的两个模糊数之间的距离,提出了模糊线性回归模型的一个约束最小二乘估计方法,该方法不仅能使估计的模糊参数的宽度具有非负性而且估计的模糊参数的中心线与传统的最小二乘估计相一致。最后,通过数值例子说明了所提方法的具体应用。     

基于模糊集相容性的模糊控制规则优化方法

在简要介绍模糊模型的完备性和相容性的基础上 ,根据模糊集贴近度 ,提出模糊集相容性的概念 ;通过对模糊控制规则表特征的分析 ,进一步完善规则相容性概念及其定量评价方法 ;最后给出模糊控制规则模型自寻优优化方法。仿真结果表明 ,该方法可以大大提高控制系统的控制性能。     

行波型热声发动机的分布参数法热力分析

在现有热声网络模型的基础上 ,对行波型热声发动机采用分布参数法进行了详细地分析 ,得到了较为完整的分布参数法网络模型 ,并给出了该模型的定性关系式 ,所得结果与采用集总参数法的结果有很大差异。分析表明 ,分布参数法更适合于一般的系统情况 ,集总参数法仅仅在一定条件下才适用。文中对一个实际系统应用分布参数法进行了分析 ,得到一些结论 ,对于我们设计行波型热声发动机有非常重要的理论指导意义     

Using activity focus networks to pressure terrorist organizations

The predominant idea for using network concepts to fight terrorists centers on disabling key parts of their communication networks. Although this counternetwork strategy is clearly a sound approach, it is vulnerable to missing, incomplete, or erroneous information about the network. This paper describes a different and complementary application of network concepts to terrorist organizations. It is based on activity focus networks (AFNs), which represent the complex activity system of an organization. An activity focus is a conceptual or physical entity around which joint activity is organized. Any organization has a number of these, which are in some cases compatible and in some cases incompatible. The set of foci and their relations of compatibility and incompatibility define the AFN. A hypothetical AFN for a terrorist organization is specified and tested in a simulation called AQAS. It shows that certain activity foci, and in particular one combination, have high potential as pressure points for the activity system. The AFN approach complements the counternetwork approach by reducing the downside risk of incomplete information about the communication network, and enhancing the effectiveness of counternetwork approaches over time. Steven R. Corman is Professor in the Hugh Downs School of Human Communication at Arizona State University and Chair of the Organizational Communication Division of the International Communication Association. His research interests include communication networks and activity systems, high-resolution text and discourse analysis, and modeling and simulation of human communication systems.     

一阶形式系统K~*及其完备性

模糊命题演算的形式系统L＊已经在模糊逻辑与模糊推理的结合研究中得到了成功的应用.本文考虑与系统L＊相应的一阶逻辑理论,建立了一阶形式系统K＊,并证明了这个系统的完备性.     

模糊关系矩阵传递闭包的Warshall算法

通过对照关系的传递闭包和模糊关系的传递闭包，把求关系矩阵的传递闭包的算法完整地推广到模糊关系矩阵上。     

On I-fuzzy topologies derived from a decreasing family of I-topologies

The aim of this paper is to study I-fuzzy topologies (fuzzy topologies in ostak's sense) derived from decreasing families of I-topologies (fuzzy topologies in Chang's sense), defined on a set X.