Repetitive control design for variable instantaneous frequencies signals

International Journal of Control, Automation and Systems - Vibration disturbances with variable instantaneous frequencies can be found in many industrial applications. Therefore, rejecting...     

Time-variant global reliability sensitivity analysis of structures with both input random variables and stochastic processes

Structural and Multidisciplinary Optimization - The ubiquitous uncertainties presented in the input factors (e.g., material properties and loads) commonly lead to occasional failure of mechanical...     

A method for stochastic multiple criteria decision making based on dominance degrees

This paper proposes a method for solving the stochastic multiple criteria decision making (SMCDM) problem, where consequences of alternatives with respect to criteria are represented by random variables with probability distributions. Firstly, definitions and related analysis of dominance degree of one probability distribution over another are given. Then, by calculating the dominance degrees, the dominance degree matrix of alternative pairwise comparisons with respect to each criterion is built. Further, using PROMETHEE II method, an overall dominance degree matrix of alternative pairwise comparisons is constructed, and a net flow of each alternative is calculated. Based on the obtained net flows, a ranking of alternatives is determined. Finally, numerical examples for the three cases are given to illustrate the use of the proposed method.     

3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor beta

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) on a series of agonists of thyroid hormone receptor beta (TRbeta), which may lead to safe therapies for non-thyroid disorders while avoiding the cardiac side effects. The reasonable q(2) (cross-validated) values 0.600 and 0.616 and non-cross-validated r(2) values of 0.974 and 0.974 were obtained for CoMFA and CoMSIA models for the training set compounds, respectively. The predictive ability of two models was validated using a test set of 12 molecules which gave predictive correlation coefficients (r(pred)(2)) of 0.688 and 0.674, respectively. The Lamarckian Genetic Algorithm (LGA) of AutoDock 4.0 was employed to explore the binding mode of the compound at the active site of TRbeta. The results not only lead to a better understanding of interactions between these agonists and the thyroid hormone receptor beta but also can provide us some useful information about the influence of structures on the activity which will be very useful for designing some new agonist with desired activity.     

Pulsed laser technique application to liquid and gaseous flows and the scattering power of seed materials

Mie scattering computations have been performed for light scattered by small particles from a pulsed sheet of laser illumination and collected and imaged by a camera lens. From these computations the smallest particles that can be photographed in various fluid measurement situations, including air and water, have been determined in terms of system parameters such as laser power, light sheet geometry, f/No., and photographic film properties. The particle scattering requirements of the individual particle image mode and the speckle mode are compared.     

鄂尔多斯盆地东南部长7油层组沉积相研究

为了明确鄂尔多斯盆地东南部长7油层组沉积体系类型和沉积相展布特征,总结其沉积演化规律,以沉积学的基本原理和方法为指导,综合运用地球化学、盆地分析等理论和方法,通过野外露头、钻井、测井等资料的综合分析,认为鄂尔多斯盆地东南部长7油层组主要发育三角洲和湖泊沉积体系,可进一步划分为3类亚相,其中以三角洲前缘和深湖2种亚相为主．     

Global stabilization of a chain of integrators with input saturation and disturbances: A new approach

In this article, we solve the problem of global stabilization for a chain of integrators in the presence of input saturation and disturbances. A novel and elegant approach to solve this problem, in the absence of disturbances, was proposed by Teel (1992) using saturation functions and coordinate transformation. With Teel’s work as a foundation, many results have been proposed to improve the performance of controllers for a chain of integrators. Naturally, all such approaches also inherited the limitations of Teel’s approach. Most importantly, in the presence of uncertainties and disturbances, the transformation introduced in Teel (1992) would considerably shrink the region where the controller is unsaturated and, severely limit the level of uncertainties and disturbances which can be tolerated. In order to overcome these difficulties, a conceptually different approach which does not rely on the coordinate transformation is presented in this work. Specifically, modified saturation functions are directly applied to the tracking error of actual states as opposed to transformed fictitious states to develop a globally stable controller. The proposed controller is less conservative in terms of the level of uncertainties and disturbances which can be handled. In addition, arbitrarily good disturbance rejection in the unsaturated region can be achieved theoretically. Comparative simulation studies performed on a third order integrator chain verified the effectiveness of the proposed scheme.     

广东省电网建设与经济发展关系实证研究

以广东省1993--2011年相关时间序列数据为基础,建立了反映电网建设水平与社会经济发展关系的向量自回归（VAR）模型,在VAR模型的基础上,分析了广东省电网建设指标与社会经济发展指标的格兰杰因果关系,运用脉冲响应函数和方差分解方法分析了电网建设与社会经济发展之间的动态影响。研究结果表明,电网建设是经济增长的基础条件之一,在电网建设与经济增长的相互作用中,电网建设对经济增长的促进作用更为显著。     

基于遗传算法的关联议题并发谈判

基于遗传算法的并发谈判在电子商务应用中具有独特的优势,但已有的研究尚未考虑议题之间的相关性、动态权重的变化规则依赖于对手信息的获取,极大地限制了其使用价值.对此,提出议题分组的方法以解决议题的相关性问题,而议题权重的变化则采取从历史资源中发掘知识的方法进行动态调整.构建了基于遗传算法的关联性议题并发谈判模型,给出了模型的形式化描述、谈判算法设计和动态权重更新方案.通过对模型的实验和比较分析,证实了该方案能够更方便地满足用户谈判的多样性需求,解决谈判中议题关联性的问题,而且能够快速、有效地得出最优谈判结果.     

Probabilistic characterisation of model error using Gaussian mixture model—With application to Charpy impact energy prediction for alloy steel

A novel approach to characterise the model prediction errors using a Gaussian mixture model is proposed. The motivation for this work lies behind many data models that are developed through prediction error minimisation with the assumption of a normal noise distribution. When the noise is non-normal, which may often be the case in complicated data modelling scenarios, the model prediction errors may contain rich information, which can be further exploited for model refinement and improvement. The key contents presented in this paper include: choosing the relevant variables to form the error data, optimising the number of Gaussian components required for the error data modelling, and fitting the Gaussian mixture parameters using an expectation-maximisation algorithm. Application of the proposed method for further model improvement, within the framework of hybrid deterministic/stochastic modelling, is also discussed. Preliminary results on the real industrial Charpy impact energy data for heat-treated steels show its effectiveness for model error characterisation, and the potential for model performance improvement in terms of prediction accuracy as well as providing accurate prediction confidence intervals.