一种模糊自动机的新模型

通过对秃头悖论的讨论分析,对传统自动机模式是否适用于模糊自动机进行分析论证,指出传统自动机模型的缺陷在于没有模糊性,不能处理模糊的事物,并对模糊自动机的旧模型提出质疑,因为旧模型固定的隶属度无法表达模糊事物的变化过程,最后从量变和质变角度提出一种模糊自动机的新模型。     

基于正态分布对模糊概念自动计算的FPDA应用设计

计算机控制系统具有自动机的特征,可以用有限自动机理论来对其进行描述,有限自动机是计算机科学各个方面的重要基石。但除确定性的有限自动机理论外,还有许多模糊事件应该由模糊自动机的隶属函数来解决,文中将重点放在具有正态分布特征的事件上。提出了一种实现自动运算的模糊自动机模型,若要在正态分布中得到“可能发生”和“很可能发生”这类模糊型事件的概率,可以只用这种模型实现自动计算。     

实例化过程模型的时间自动机描述方法研究

语法结构正确的过程模型并不能保证过程运作的实际执行,因为没有考虑实例化阶段的时间资源安排.传统的过程自动机描述法不足以分析实例化过程模型.针对这种情况,提出用时间自动机描述过程模型语义的方法,设计了生成时间自动机的算法,分析了这种描述方法在模型检验中的应用.     

Mizumoto格值有限自动机及其最小化

提出取值为格半群的Mizumoto格值有限自动机的概念,得到基于模糊字符串的Mizumoto格值有限自动机的扩张模型,并详细讨论了其性质。同时建立了扩张Mizumoto格值有限自动机与标准扩张Mizumoto格值有限自动机的等价性,在此基础上给出了其最小化算法。     

汉字模糊有穷自动机的研究

汉字的计算机输入是中文信息处理的关键问题之一,而汉字计算机输入的数学模型对汉字的计算机输入的研究有重要的意义。对汉字输入数学模型的分类进行了研究。研究了一般汉字有穷自动机,在此基础上把模糊有穷自动机的概念引入输入模型,并给出汉字模糊有穷自动机的概念。新的模型是以前给出的汉字自动机模型的推广,较之以前的数学模型,能刻画出汉字智能输入、词句输入,表达能力进一步增强,为汉字的智能处理提供了数学模型。     

机器人化柔性装配过程的模糊自动机模型

机器人化柔性装配系统是现代制造系统的重要研究内容之一．装配过程的建模是许多研究工作的基础．本文在分析装配过程的特点的基础上，将模糊自动机的理论和方法应用于装配过程的建模研究中，提出了一种机器人化柔性装配过程的模糊自动机模型     

基于模糊度量的软件漏洞检测技术研究

本文根据有限状态自动机和模型检测的思想,结合模糊数学对行为分析的优势,提出基于模糊度量的软件漏洞检测技术,并利用漏洞属性分解和模糊状态转移函数使此技术具有自学习机制和更高效广泛的检测能力。实验测试了利用模糊度量的软件漏洞检测技术可以提高漏洞发现率和给出漏洞的危急程度。     

基于云模型元胞自动机的农田图像边缘检测方法

为了满足智能农业机械自动导航系统的应用需求,本文提出了一种基于云模型元胞自动机的农田图像边缘检测方法。该方法采用云模型模糊逻辑对特征信息进行模糊推理,并通过元胞自动机的自动演化过程得到图像边缘。实验表明,该方法应用于农田图像边缘检测中效果较好。     

基于自动机的分析与综合因素神经网络的自动实现方法

本文讨论了因素神经网络与自动机的关系及分析与综合因素神经网络的自动机算法。刻画了因素神经网络的状态集合及正则模糊文法的生成式链，给出了自动机算法的形式化，使对神经网络的分析与综合可在计算机上得以自动实现。     

模糊有限自动机的最小化算法优化

现有的模糊自动机最小化算法没有涉及到对模糊自动机状态的隶属度迁移和变化的讨论,优化的模糊自动机最小化算法弥补了这类算法的不足之处。该算法将模糊有限自动机首先转化为单个初始状态的模糊自动机,然后再将转化后的模糊自动机化简为最小模糊自动机,算法在转化过程中单独讨论了模糊自动机状态隶属度的转化方式,使得算法更加严谨和简化。     

An unsupervised classifier for remote-sensing imagery based on improved cellular automata

Traditional unsupervised classification algorithms for remote-sensing images, such as k-means (KM), have been widely used for massive data sets due to their simplicity and high efficiency. However, they do not usually take the interaction between neighbouring pixels into account, but only take individual pixels as the elements for clustering and classification. According to Tobler’s first law of geography, everything is related to everything else, but near things are more related than distant things. To make use of the spatial interaction between pixels, the cellular automata method can be employed to improve the accuracy of image classification. In cellular automata theory, the state of a cell at the next moment is determined by its current state and that of its neighbours. In traditional cellular automata methods, which are based on a standard neighbour configuration, even if the influence of neighbouring cells on the central cell is measured, the weights of these influences are the same. Hence, this article proposes an improved cellular automata method for image classification by allowing the cellular automata to diffuse in a geometrical circle, and by measuring the influence of the neighbouring cells using a fuzzy membership function. The proposed classifier was tested with typical Landsat Enhanced Thematic Mapper Plus (ETM+) and high-resolution images. The experiments reveal that the new classifier can achieve better results, in terms of overall accuracy and kappa coefficient, than cellular automata classifier based on Moore type (CAS), KM, and fuzzy c-means.     

模糊Bayes 理论在遥感影像变化检测中的应用

针对传统基于Bayes 决策规则的遥感影像变化检测方法中参数估计的不足以及分类过程中的硬划分问题,采用动态更新变化和未变化两类像元模糊子集的方法,实现对两类像元模糊子集中参数的动态更新,利用估计参数获得各子集的后验概率函数,再将后验概率函数转化为模糊子集的模糊隶属函数,从而获得各子集的指标函数,根据指标函数对影像中未分类的像元值进行判断,实现遥感影像的变化区域提取。实验结果表明：与现有的基于Bayes 决策规则的遥感影像变化检测方法及ERDAS 软件生成结果相比,提出的方法具有更好的变化检测精度。     

基于元胞自动机和模糊理论的人群疏散仿真

基于元胞自动机和模糊理论建立了人群疏散模型,对教学楼内的人群疏散过程进行了模拟。该模型根据人员对建筑物的熟悉程度、周围人员的吸引力设计元胞行为准则,并且采用模糊隶属度定义人员的体能状态及人员对环境的熟悉程度。实验结果表明,该仿真模型能够较好地模拟紧急状况下的人群疏散过程。     

A formal model of computing with words

Classical automata are formal models of computing with values. Fuzzy automata are generalizations of classical automata where the knowledge about the system's next state is vague or uncertain. It is worth noting that like classical automata, fuzzy automata can only process strings of input symbols. Therefore, such fuzzy automata are still (abstract) devices for computing with values, although a certain vagueness or uncertainty are involved in the process of computation. We introduce a new kind of fuzzy automata whose inputs are instead strings of fuzzy subsets of the input alphabet. These new fuzzy automata may serve as formal models of computing with words. We establish an extension principle from computing with values to computing with words. This principle indicates that computing with words can be implemented with computing with values with the price of a big amount of extra computations.     

基于模糊神经网络PID算法的电阻炉温控系统

由于电阻炉温控系统是一个大惯性、大滞后、时变、且非线性的系统,采用传统PID控制不能解决系统的非线性、时变和PID参数的在线整定难等问题,为此提出一种控制算法—模糊神经网络PID算法。可根据电阻炉的温度的偏差及其变化率实时对PID的3个参数进行优化,达到具有最佳组合的PID控制,从而实现PID控制的自适应和智能化性能。使用MatLab的simulink仿真,通过传统PID与模糊神经网络PID阶跃响应曲线的比较,表明系统采用模糊神经网络PID算法具有更好的动、静态特性和自适应性,对突加的外部的扰动具有良好的抗干扰能力,具有实用价值。     

无随机预言模型下基于模糊身份的签名方案

在随机预言模型下,Hash函数被视为一个完全随机的理想模型,实际应用中却无法构造。利用椭圆曲线上的双线性对性质及门限秘密共享的思想,以Waters的签名方案为基础,设计了一种无随机预言模型的模糊身份签名方案。与已有的模糊签名方案相比,该方案的构造没有采用Hash函数,避免了Hash函数返回值无随机性的缺点;且系统公开参数少,安全性可规约到计算Diffie-Hellman（CDH）困难假定,从而能更好地满足实际应用需求。     

IF-topologies and IF-automata

The purpose of this work is to indicate that a study of IF-automata (also called, intuitionistic fuzzy automata) can be carried out much on the same lines as the one done for fuzzy automata in Srivastava and Tiwari (Proceedings of 2002 AFSS international conference on fuzzy systems. Lecture notes in artificial intelligence, vol 2275. Springer, Berlin, pp 485–490, 2002). It is also shown that two IF-topologies (also called, intuitionistic fuzzy topologies) can be associated with the state-sets of IF-fuzzy automata whose level topologies have interesting relationships with the topologies introduced by Srivastava and Tiwari (above mentioned) for fuzzy automata.     

Determinization of fuzzy automata with membership values in complete residuated lattices

In this paper we introduce a new method for determinization of fuzzy finite automata with membership values in complete residuated lattices. In comparison with the previous methods, developed by Bělohlávek [R. Bělohlávek, Determinism and fuzzy automata, Information Sciences 143 (2002), 205-209] and Li and Pedrycz [Y.M. Li, W. Pedrycz, Fuzzy finite automata and fuzzy regular expressions with membership values in lattice ordered monoids, Fuzzy Sets and Systems 156 (2005), 68-92], our method always gives a smaller automaton, and in some cases, when the previous methods result in infinite automata, our method can result in a finite one. We also show that determinization of fuzzy automata is closely related to fuzzy right congruences on a free monoid and fuzzy automata associated with them, and in particular, to the concept of the Nerode’s fuzzy right congruence of a fuzzy automaton, which we introduce and study here.