A design and analysis of objective function-based unsupervised neural networks for fuzzy clustering

Fuzzy clustering has played an important role in solving many problems. In this paper, we design an unsupervised neural network model based on a fuzzy objective function, called OFUNN. The learning rule for the OFUNN model is a result of the formal derivation by the gradient descent method of a fuzzy objective function. The performance of the cluster analysis algorithm is often evaluated by counting the number of crisp clustering errors. However, the number of clustering errors alone is not a reliable and consistent measure for the performance of clustering, especially in the case of input data with fuzzy boundaries. We introduce two measures to evaluate the performance of the fuzzy clustering algorithm. The clustering results on three data sets, Iris data and two artificial data sets, are analyzed using the proposed measures. They show that OFUNN is very competitive in terms of speed and accuracy compared to the fuzzy c-means algorithm.     

EXTENSION OF THE RELATIONAL DATABASE AND ITS ALGEBRA WITH ROUGH SET TECHNIQUES

This paper describes a database model based on the original rough sets theory. Its rough relations permit the representation of a rough set of tuples not definable in terms of the elementary classes, except through use of lower and upper approximations. The rough relational database model also incorporates indiscernibility in the representation and in all the operators of the rough relational algebra. This indiscernibility is based strictly on equivalence classes which must be defined for every attribute domain. There are several obvious applications for which the rough relational database model can more accurately model an enterprise than does the standard relational model. These include systems involving ambiguous, imprecise, or uncertain data. Retrieval over mismatched domains caused by the merging of one or more applications can be facilitated by the use of indiscernibility, and naive system users can achieve greater recall with the rough relational database. In addition, applications inherently “rough” could be more easily implemented and maintained in the rough relational database.     

不确定移动对象概率Skyline集的查询更新

Skyline查询的研究已从传统的静态Skyline操作延伸到动态的、不确定数据集上的Skyline查询和计算上。研究了移动环境下,查询点位置固定、目标点处于运动状态并且位置不确定情况下的连续概率Skyline计算问题。这个过程中,移动对象与查询对象之间的距离随时间不断变化。移动对象由于其运动状态导致位置无法精确定位,因此移动对象之间的支配关系只能采用概率形式表示,且随时间不断变化。给出了移动对象间的支配概率的定义,以及移动对象Skyline概率的定义,并定义了触发事件来记录对象支配概率发生变化的时刻,实现概率Skyline计算的连续跟踪和动态更新。提出了基于事件触发的连续概率Skyline查询算法(event triggered continuous probabilistic Skyline query for uncertain moving object,U-ECPS),对移动环境下的Skyline集进行连续查询和更新。大量的实验结果验证了U-ECPS算法的有效性。     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.     

水工钢闸门主梁模糊失效概率计算方法研究

为合理计算水工钢闸门主梁模糊失效概率,分别将主梁相对变形当作一个随机变量及三个变量的组合,采用积分法、当量随机化方法及蒙特卡罗法进行了计算。当相对变形为一个随机量时,采用积分法及当量随机化方法计算,两者的差别在于积分法用隶属函数描述模糊限值,当量随机化方法是将模糊限值当量作为一个随机量。当相对变形看作三个变量的组合时采用蒙特卡罗法进行计算,该方法考虑了三个变量的分布特性,更符合实际情况,模糊限值也用随机量表示。计算表明,积分法与当量随机化方法结果相近,验证了当量随机化方法的精度;蒙特卡罗法结果与相对变形服从正态分布时、用当量随机化方法计算的结果接近,故主梁相对变形服从正态分布更为合理。三种计算方法中,当量随机化方法计算失效概率相较于其它方法有计算过程简便,效率高的优点。     

Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.     

DETECTOR: A knowledge-based system for injection molding diagnostics

A knowledge-based system (KBS) for diagnosis of multiple defects in injection molding is presented. The general scheme for knowledge representation based on fuzzy set theory has been shown useful in representing inexact and incomplete information for developing the KBS. An optimality criterion is created for selecting a simple and best cover to explain the given problem. An efficient search algorithm for finding such cover is also discussed.     

多机器人网络中资源公平分配的研究

就如何实现多机器人网络中各独立任务资源的公平分配及其服务质量最优化提出了一种新方法。该方法通过对增益控制参数的模糊控制,增强了系统的鲁棒性,并尽可能快速平稳地实现各项独立任务所需资源的公平分配。     

液压支架工作状态模糊识别系统研究

针对目前综采工作面液压支架压力监测系统只能监测综采工作面压力,不能对液压支架工作状态进行识别的问题,设计了一种液压支架工作状态模糊识别系统。该系统可对现有的综采工作面液压支架压力监测系统监测到的压力数据进行模糊识别,根据模糊识别输出值即可判断液压支架的5种工作状态,即降架、移架、升架、增阻、卸压保持;当液压支架处于增阻工作状态且增阻时间过长时,该系统可及时通知液压支架操作工增大液压支架压力,辅助实现顶煤破碎。测试结果验证了该系统的可行性。