Inference for Weibull distribution under generalized order statistics

Based on generalized order statistics from Weibull distribution the approach of Bayesian and non-Bayesian estimation are discussed. We present a simple and efficient simulational algorithm for generating a generalized order statistics sample from any continuous distribution. Specializations to Bayesian and non-Bayesian estimators, some lifetime parameters and confidence intervals of progressive II censoring and record values are obtained and compared with the existing results. Two examples are given to illustrate the proposed estimators and the simulation algorithm.     

Integrating customer's preferences in the QFD planning process using a combined benchmarking and imprecise goal programming model

Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products to achieve higher customer satisfaction by integrating various functions of an organization. The engineering characteristics (ECs) affecting the product performances are designed to match the customer attributes (CAs). However, from the viewpoint of the QFD team, product design processes are performed in imprecise environments, and more than one factor must be taken into account in determining the target levels of ECs, especially the limited resources and increased market competition. This paper presents an imprecise goal programming (GP) approach to determine the optimum target levels of ECs in QFD for maximizing customer satisfaction under resource limitation and considerations of market competition. Based on benchmarking data of CAs, the concept of satisfaction functions is utilized to formulate explicitly the customer's preferences and to integrate the competitive analysis of target market into the modelling and solution process. In addition, the relationships linking CAs and ECs and the ECs to each other are integrated by functional relationships. The proposed approach will be illustrated through a car door design example.     

飞行器姿态控制系统中的一种计算机仿真研究

针对飞行器姿态控制系统的参数时变性和不确定性干扰等特点,本文给出了一种基于Ackermann规则的滑模变结构控制器,并在设计滑模面时,引入积分项来消除干扰等因素给系统带来的稳态误差;为消除抖动,在控制器中引入模糊系统来实现去抖;同时设计灰色补偿控制项来抵消不确定项对系统造成的不利影响。最后进行了计算机数字仿真,结果表明本文所设计的控制器具有很好的效果。     

基于Agent的网络新闻信息管理系统功能分析

该文从网络新闻信息管理现状出发,结合Agent技术的特性,通过对基于Agent的信息管理系统设计理念的分析,总结并归纳了基于使用者角度的Agent网络新闻信息管理系统三大功能需求;随之,就系统的四个功能模块进行了详细阐述,最后进行系统的兼容性分析。     

基于带偏好自适应评价的公交线路选择问题研究

在智能交通系统中公汽线路选择是一个重要的问题。该文首先利用公汽的行驶线路进行深度优先搜索．得到从开始站点到结束站点所有可能的乘车线路。然后分别考虑乘车时间Time和乘车价格Price来评价这些乘车线路优劣,最终得到题目要求的最佳线路。为了能够综合考虑Time和Price,通过引入用户期望度p,提出了一种带偏好的自适应评价函数来对基于Time和Price的评价方法进行进一步的改进,这个带偏好的自适应评价函数合理表达了查询者的主观意向、乘车线路差异,从而可以满足不同查询者的不同需求。最后通过仿真实验对该文方法进行了有效性验证。     

灵活运用Excel分析学生成绩

考试结束后,通过对学生考试成绩的分析,教师可以对该课程的教学工作进行系统的总结,更好的安排下一阶段的教学工作。该文根据个人经验,介绍了如何灵活运用Excel分析学生成绩的方法与技巧,从而使教学工作变得更加简单、高效。     

Improved nonlinear trajectory tracking using RBFNN for a robotic helicopter

This paper presents a backstepping control method using radial‐basis‐function neural network (RBFNN) for improving trajectory tracking performance of a robotic helicopter. Many well‐known nonlinear controllers for robotic helicopters have been constructed based on the approximate dynamic model in which the coupling effect is neglected; their qualitative behavior must be further analyzed to ensure that the unmodeled dynamics do not destroy the stability of the closed‐loop system. In order to improve the controller design process, the proposed controller is developed based on the complete dynamic model of robotic helicopters by using an RBFNN function approximation to the neglected dynamic uncertainties, and then proving that all the trajectory tracking error variables are globally ultimately bounded and converge to a neighborhood of the origin. The merits of the proposal controller are exemplified by four numerical simulations, showing that the proposed controller outperforms a well‐known controller in (J. Robust Nonlinear Control 2004; 14 (12):1035–1059). Copyright © 2009 John Wiley & Sons, Ltd.     

Delay-dependent Non-fragile H∞ Filtering for Uncertain Fuzzy Systems Based on a Switching Fuzzy Model and Piecewise Lyapunov Function

This paper is concerned with the non-fragile H∞ filter design problem for uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with time delay. To begin with, the T-S fuzzy system is transformed to an equivalent switching fuzzy system. Then, based on the piecewise Lyapunov function and matrix decoupling technique, a new delay-dependent non-fragile H∞ filtering method is proposed for the switching fuzzy system. The proposed condition is less conservative than the previous results. Since only a set of LMIs is involved, the filter parameters can be solved directly. Finally, a design example is provided to illustrate the validity of the proposed method.     

The structure of canalizing functions

The structure of a canalizing function is discussed. Using a new matrix product, namely semitensor product, the logical function is expressed in its matrix form. From its matrix expression, a criterion is obtained to test whether a logical function is a canalizing function. Then a formula is obtained to calculate the number of canalizing functions. Moreover, an algorithm is presented to generate canalizing functions. Finally, some results obtained are extended to seminested canalizing functions.     

A self-adaptive linear evolutionary algorithm for solving constrained optimization problems

In many real-world applications of evolutionary algorithms, the fitness of an individual requires a quantitative measure. This paper proposes a self-adaptive linear evolutionary algorithm (ALEA) in which we introduce a novel strategy for evaluating individual’s relative strengths and weaknesses. Based on this strategy, searching space of constrained optimization problems with high dimensions for design variables is compressed into two-dimensional performance space in which it is possible to quickly identify ‘good’ individuals of the performance for a multiobjective optimization application, regardless of original space complexity. This is considered as our main contribution. In addition, the proposed new evolutionary algorithm combines two basic operators with modification in reproduction phase, namely, crossover and mutation. Simulation results over a comprehensive set of benchmark functions show that the proposed strategy is feasible and effective, and provides good performance in terms of uniformity and diversity of solutions.