Exponential stabilization of uncertain time‐delay linear systems with Markovian jumping parameters

This paper studies the exponential stabilization problem of uncertain time‐delay linear systems with Markovian jumping parameters. A novel delay decomposition approach is developed to derive delay‐dependent conditions under which the closed‐loop control system is mean square exponentially stable for all admissible uncertainties. It is shown that the feedback gain matrices and the decay rate can be obtained by solving coupled linear matrix inequalities. Moreover, the difficulties arising from searching for tuning parameters in the existing methods are overcome. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment

We study the group decision making problem under intuitionistic fuzzy environment. Based on entropy and cross entropy, we give two methods to determine the optimal weights of attributes, and develop two pairs of entropy and cross entropy measures for intuitionistic fuzzy values. Then, we discuss the properties of these measures and the relations between them and the existing ones. Furthermore, we introduce three new aggregation operators, which treat the membership and non-membership information fairly, to aggregate intuitionistic fuzzy information. Finally, several practical examples are presented to illustrate the developed methods.     

Financial distress prediction using support vector machines: Ensemble vs. individual

Financial distress prediction (FDP) is of great importance to both inner and outside parts of companies. Though lots of literatures have given comprehensive analysis on single classifier FDP method, ensemble method for FDP just emerged in recent years and needs to be further studied. Support vector machine (SVM) shows promising performance in FDP when compared with other single classifier methods. The contribution of this paper is to propose a new FDP method based on SVM ensemble, whose candidate single classifiers are trained by SVM algorithms with different kernel functions on different feature subsets of one initial dataset. SVM kernels such as linear, polynomial, RBF and sigmoid, and the filter feature selection/extraction methods of stepwise multi discriminant analysis (MDA), stepwise logistic regression (logit), and principal component analysis (PCA) are applied. The algorithm for selecting SVM ensemble's base classifiers from candidate ones is designed by considering both individual performance and diversity analysis. Weighted majority voting based on base classifiers’ cross validation accuracy on training dataset is used as the combination mechanism. Experimental results indicate that SVM ensemble is significantly superior to individual SVM classifier when the number of base classifiers in SVM ensemble is properly set. Besides, it also shows that RBF SVM based on features selected by stepwise MDA is a good choice for FDP when individual SVM classifier is applied.     

Supply chain trust diagnosis (SCTD) using inductive case-based reasoning ensemble (ICBRE): The case of general competence trust diagnosis

General competence trust among supply chain partners, referring to the trust that a partner holds the general ability of fulfilling contracts, is a critical factor to ensure effective cooperation in a supply chain, especially in the current financial crisis. The method of supply chain trust diagnosis (SCTD) is to evaluate whether or not a partner holds such competence. This research devotes to an early investigation on diagnosing competence trust of supply chain with the method of inductive case-based reasoning ensemble (ICBRE). The so-called supply chain trust diagnosis with inductive case-based reasoning ensemble consists of five levels, that is, information level, the level of ratios of general competence states, the level of inductive case-based reasoning, ensemble level, and diagnosis result level. Knowledge for diagnosing competence trust, which composes of a case base, is hidden in data represented by ratios of general competence states. Inductive approach is combined with randomness to construct diverse and good member methods of inductive case-based reasoning. Finally, simple voting is used to integrate outputs of member inductive case-based reasoning methods in order to produce the final diagnosis on whether or not a partner holds the general ability of fulfilling contracts. We statistically validated results of the method of supply chain trust diagnosis with inductive case-based reasoning ensemble by comparing them with those of multivariate discriminant analysis, logistic regression, single Euclidean case-based reasoning, and single inductive case-based reasoning. The results indicate that the method of supply chain trust diagnosis with inductive case-based reasoning ensemble significantly improves predictive capability of case-based reasoning in this problem and outperforms all the comparative models by group decision of several decision-making agents and non-strict assumptions like statistical methods.     

基于改进LS-SVM的制粉出力软测量建模

针对火电厂双进双出钢球磨煤机制粉出力较难直接测量的问题,拟建立其最小二乘支持向量机(LS-SVM)模型实现软测量.由于LS-SVM算法缺乏“稀疏性”,采用经Remez算法优化后的FIR数字滤波器与LS-SVM相结合,形成一种新的软测量建模方法——FIR-LSS-VM.仿真结果表明,经Remez优化后的FIR滤波效果更好.将该软测量方法应用于火电厂双进双出钢球磨煤机直吹式制粉系统,通过现场实验对比可知,改进的软测量模型学习速度较快且误差较小,更加适用于在线学习.     

高速动车组驾驶室设计中的人机界面分析

在高速动车组驾驶室的人机关系分析与设计中,驾驶室的空间尺度关系、视野、操纵设备的分布和人机环境等因素,将直接影响列车行驶的安全、效率、舒适和健康。应用人机关系分析与研究,合理地配置驾驶室室内环境以及操作和显示设备,将有效地提高司机操作的安全性、便利性和作业效率,从而给司机提供一个方便舒适的操作空间,减少体力、心理疲劳,降低人为误操作带来的安全隐患,提高系统运行的可靠性,使人-机匹配达到最优,以保证车辆行驶的安全。     

On the merits of ancient Chinese eye acupressure practices

Chinese schoolchildren and adults with strenuous visual tasks routinely perform massage-and-pressure exercises on selected acupressure points around the eyes. This practice, taught by the Jing-Luo school of acupuncture for more than 4000 years, is claimed to prevent and cure myopia and other afflictions thought to result from visual close work. A four-week pilot experiment was carried out with the aim of designing a proper study on the possible short-term benefits of eye acupressure programmes. Questionnaire data revealed that the subjects did experience various eye/vision symptoms as a result of the 90 min experimental task. This could not be verified by the measurements of accommodation precision and critical flicker fusion, nor could any beneficial effects of acupressure be seen over the four experimental weeks.     

VB程序在铁路货车制造行业中小设备中的应用

介绍利用VB语言在铁路货车制造行业中小设备中的软件开发方案的实现,以及对铁路货车制造行业相关专业性要求适应的实现。     

基于SINS的车辆导航系统性能增强算法研究

SINS的车辆导航系统的参数误差随时间积累,使得车辆的定位融合算法存在非线性及易发散等问题,而无法长时间得到高精度、高可靠性的导航参数。本文设计了一种带速度约束条件的SINS车辆导航滤波算法来增强SINS车辆导航系统的定位精度与持续工作能力,建立了具体的系统方程与观测方程,并进行了Matlab仿真实验。仿真结果表明,该方法能够有效抑制发散现象,速度误差和经纬度误差分别能够保持在2m/s和15m的范围内,从而保证了车辆导航的精度要求。     

基于分形扫描的高灰度平板显示的硬件实现

本文将分形算法应用于2048级高灰度平板显示的扫描映射,使用平板显示系统灰度图像的最优扫描结构及分形模型,以解决平板显示系统扫描形成灰度图像过程中的时间冗余问题。由分形扫描核心模块,得到了相应的每个扫描时间对应的子空间码和位码序列进行扫描,然后通过检测模块验证了2048级高灰度分形扫描方法的准确性,最终由硬件系统验证了2048级高灰度分形扫描的可实现性。