Semisupervised Multicategory Classification With Imperfect Model

Semisupervised learning has been of growing interest over the past years and many methods have been proposed. While existing semisupervised methods have shown some promising empirical performances, their development has been based largely on heuristics. In this paper, we investigate semisupervised multicategory classification with an imperfect mixture density model. In the proposed model, the training data come from a probability distribution, which can be modeled imperfectly by an identifiable mixture distribution. Furthermore, we propose a semisupervised multicategory classification method and establish its generalization error bounds. The theoretical analysis illustrates that the proposed method can utilize unlabeled data effectively and can achieve fast convergence rate.     

Homography-Based Visual Servo Control With Imperfect Camera Calibration

In this technical note, a robust adaptive uncalibrated visual servo controller is proposed to asymptotically regulate a robot end-effector to a desired pose. A homography-based visual servo control approach is used to address the six degrees-of-freedom regulation problem. A high-gain robust controller is developed to asymptotically stabilize the rotation error, and an adaptive controller is developed to stabilize the translation error while compensating for the unknown depth information and intrinsic camera calibration parameters. A Lyapunov-based analysis is used to examine the stability of the developed controller.      

Rough Problem Settings for ILP Dealing With Imperfect Data

This paper applies rough set theory to Inductive Logic Programming (ILP, a relatively new method in machine learning) to deal with imperfect data occurring in large real-world applications. We investigate various kinds of imperfect data in ILP and propose rough problem settings to deal with incomplete background knowledge (where essential predicates/clauses are missing), indiscernible data (where some examples belong to both sets of positive and negative training examples), missing classification (where some examples are unclassified) and too strong declarative bias (hence the failure in searching for solutions). The rough problem settings relax the strict requirements in the standard normal problem setting for ILP, so that rough but useful hypotheses can be induced from imperfect data. We give simple measures of learning quality for the rough problem settings. For other kinds of imperfect data (noise data, too sparse data, missing values, real-valued data, etc.), while referring to their traditional handling techniques, we also point out the possibility of new methods based on rough set theory.     

基于Word Basic的试题库设计

图、表和公式一直是计算机语言用来设计制作试题库的难点。而WORD BASIC由于是基于Word的计算语言,却能很好的解决这个问题,由各种基于Windows的软件制作基本的试题库试题,这些试题可以很好地组合到一个WORD文件中,由Word Basic编制的试题库软件对该文件进行选择处理,组成了所需要的试卷,这些试卷可以包括文字,图表,公式,甚至声音和动画。本文介绍了基于WORD BASIC的试题库的设计思想和具体实现。     

基于非完备性测试的一种分布式计算机系统诊断算法的设计

利用现有的商用并行、分布式计算机系统本身所固有的冗余可以实现低成本的容错。为了提高整个分布式计算机系统的可靠性,将系统中的故障结点与正确结点隔离至关重要。文章提出了一个有效的分布式系统级故障诊断算法：在利用系统中各结点机有限的故障检测能力的基础上,将所有的故障结点从系统中隔离,并测试了该算法对系统性能的影响。     

针对动态系统的多故障诊断模型与优化算法

一般的静态故障诊断模型无法描述状态随时间变化的系统,为此用隐马尔可夫模型对动态变化的系统状态进行建模,给出了动态多故障诊断问题的形式化描述;该问题的目标函数是典型的集合覆盖问题,属于NP难解问题。通过将原始目标函数转化为若干个独立的子问题,并分别用动态规划算法进行求解,有效实现了动态系统的多故障诊断;与现有的方法相比,该方法在不影响检测率和隔离率的前提下,执行时间短,计算复杂度低,优化效果明显。     

利用JSP开发动态Web应用系统

本文通过一个实例,介绍了利用JSP开发动态Web应用系统的过程.与其他语言相比,JSP在开发动态网站方面,具有跨平台、易开发的优点.     

用面向对象的方法设计动态Web

本文基于PHP语言。探讨用面向对象的思路和方法设计数据库应用,将面向对象技术和关系数据库技术结合在一起实现动态交互式Web。     

利用JSP开发动态Web应用系统

本文通过一个实例,介绍了利用JSP开发动态Web应用系统的过程。与其他语言相比,JSP在开发动态网站方面,具有跨平台、易开发的优点。     

Imperfect Evolutionary Systems

In this paper, we propose a change from a perfect paradigm to an imperfect paradigm in evolving intelligent systems. An imperfect evolutionary system (IES) is introduced as a new approach in an attempt to solve the problem of an intelligent system adapting to new challenges from its imperfect environment, with an emphasis on the incompleteness and continuity of intelligence. We define an IES as a system where intelligent individuals optimize their own utility, with the available resources, while adapting themselves to the new challenges from an evolving and imperfect environment. An individual and social learning paradigm (ISP) is presented as a general framework for developing IESs. A practical implementation of the ISP framework, an imperfect evolutionary market, is described. Through experimentation, we demonstrate the absorption of new information from an imperfect environment by artificial stock traders and the dissemination of new knowledge within an imperfect evolutionary market. Parameter sensitivity of the ISP framework is also studied by employing different levels of individual and social learning     

基于模型诊断的元件替换与替换测试

元件替换是工农业和日常生活中经常使用的一种诊断方法,文中结合基于模型诊断理论,对元件的替换测试进行了研究,提出了元件替换与替换测试的概念,并以此为基础对诊断的判定与故障元件的确定进行了探索,证明了关于替换测试用于故障原因判定的几个定理。文中的研究结果可以帮助选择欲替换的元件,提高诊断效率,并可以将测试同修复结合来,使系统尽快恢复正常功能。     

Diagnosis of DES With Petri Net Models

The diagnosis of discrete event systems is strongly related to events estimation. This paper focuses on faulty behaviors modeled with ordinary Petri nets with some "fault" transitions. Partial but unbiased measurement of the places marking variation is used in order to estimate the firing sequences. The main contribution is to decide which sets of places must be observed for the exact estimation of some given firing sequences. Minimal diagnosers are defined that detect and isolate the firing of fault transitions immediately. Causality relationships and directed paths are also investigated to characterize the influence and dependence areas of the fault transitions. Delayed diagnosers are obtained as a consequence. Note to Practitioners-Structural tools are provided for the analysis of models used in the context of fault detection and isolation for discrete event systems. The systems that are concerned are either manufacturing processes, batch processes, digital devices, or communication protocols with single or multiple failures. Methods are proposed to decide, in a systematic way, if the considered failures can be detected and isolated according to the existing sensors. The obtained results can also be used by designers for sensor selection     

基于不完美信息博弈的网上购物信任问题分析

随着网上购物在中国的快速发展,越来越多的网上欺诈和交易纠纷也不断发生.结合完全但不完美信息动态博弈和重复博弈的思想,通过博弈模型对网上欺诈产生的原因、条件、制约因素以及治理的途径作一些解释和探讨,并对我国健全网上信用机制提出一些建议.     

基于模型诊断的动态测试策略

本文通过分析基于模型诊断的候选诊断集的特点，提出了基于模型的动态测试策略，并提出了采用关联规则挖掘的技术－－频繁模式增长法，作为解决选择测试元件过程的处理技术，巧妙地解决了动态选择的策略问题。     

用VC制作动态连接库

本文论述了用VC制作动态连接库的注意问题和方法，并给出了检测与控制I／O口的应用实例。     

A Novel Fuzzy System With Dynamic Rule Base

A new fuzzy system containing a dynamic rule base is proposed in this paper. The novelty of the proposed system is in the dynamic nature of its rule base which has a fixed number of rules and allows the fuzzy sets to dynamically change or move with the inputs. The number of the rules in the proposed system can be small, and chosen by the designer. The focus of this article is mainly on the approximation capability of this fuzzy system. The proposed system is capable of approximating any continuous function on an arbitrarily large compact domain. Moreover, it can even approximate any uniformly continuous function on infinite domains. This paper addresses existence conditions, and as well provides constructive sufficient conditions so that the new fuzzy system can approximate any continuous function with bounded partial derivatives. Finally, an example is given to show how the proposed fuzzy system can be effectively used for system modeling and control     

Dynamic Output Integral Sliding-Mode Control With Disturbance Attenuation

This technical note proposes a dynamic output feedback sliding-mode control algorithm for linear MIMO systems with mismatched norm-bounded uncertainties along with disturbances and matched nonlinear perturbations. A control law is first designed to ensure that the system behavior can satisfy the reaching and sliding condition. A scheme designed to combine the output-dependent integral sliding surface with a full-order compensator is then proposed. Through utilizing $H _{infty} $ control analytical technique, once the system is in the sliding mode, the proposed algorithm can guarantee robust stabilization and sustain the nature of performing disturbance attenuation when the solutions to two algebraic Riccati inequalities can be found. Finally, the feasibility of our proposed algorithm is illustrated using a numerical example.