Fuzzy arithmetic-based interpolative reasoning for nonlinear dynamic fuzzy systems

FAIR (fuzzy arithmetic-based interpolative reasoning)—a fuzzy reasoning scheme based on fuzzy arithmetic, is presented here. Linguistic rules of the Mamdani type, with fuzzy numbers as consequents, are used in an inference mechanism similar to that of a Takagi–Sugeno model. The inference result is a weighted sum of fuzzy numbers, calculated by means of the extension principle. Both fuzzy and crisp inputs and outputs can be used, and the chaining of rule bases is supported without increasing the spread of the output fuzzy sets in each step. This provides a setting for modeling dynamic fuzzy systems using fuzzy recursion. The matching in the rule antecedents is done by means of a compatibility measure that can be selected to suit the application at hand. Different compatibility measures can be used for different antecedent variables, and reasoning with sparse rule bases is supported. The application of FAIR to the modeling of a nonlinear dynamic system based on a combination of knowledge-driven and data-driven approaches is presented as an example.     

基于组合逻辑的故障诊断方法

针对复杂系统故障传播和故障分析的模糊性和不确定性,首先,在逻辑Petri网和模糊Petri网的理论基础上,根据逻辑Petri网的传值不确定性以及模糊Petri网对模糊信息的表示和推理能力的特点,提出模糊逻辑Petri网的概念及推理规则,考虑不同故障源对故障的影响程度,将概率信息引入模糊逻辑Petri网,对故障源赋予置信度,使故障诊断过程更符合实际。其次,利用模糊逻辑Petri网对故障诊断系统进行建模,用模糊逻辑Petri网描述了系统故障状态组合的逻辑关系,并进一步简化了系统模型的表达形式,具有良好的封装性、重构性和可维护性,在一定程度上缓解了状态组合空间爆炸问题。针对故障的传播性,采用可达性分析方法对故障信息的传播路径进行模拟论证,提高了故障诊断效率。最后,通过离心式压缩机故障诊断过程实例分析,验证了该方法的有效性和可行性,提高了故障诊断过程的准确性和高效性。     

模糊时间Petri网及其时间推理方法

Petri网是一种用网状图形表示系统模型的方法,它能够从组织结构、控制和管理的角度,精确描述系统中事件(变迁)之间的依赖(顺序)和不依赖(并发)关系。但传统的Petri网理论其不足之处在于:它的分析方法主要是可达树分析法和线性代数描述法。可达树分析法是针对某一个初始标识的,一个新的初始标识就意味着需要重新构造可达状态图;当系统存在较多     

模糊Petri网及知识表示

在建造专家系统中虽然有很多种知识表示方法，但都有不尽人意的地方，本文试图用一种新的方法－Ｐｅｔｒｉ网模型来表示知识。本文给出了Ｆｕｚｚｚｙ Ｐｅｔｒｉ网和广义Ｆｕｚｚｙ Ｐｅｔｒｉ网两种模型，并给出了相应的推理算法，一旦专家知识用Ｐｅｔｒｉ网表示后，根据Ｐｅｔｒｉ网固有的特性，我们就能处理专家系统中并行推理、无回溯推理，反向推理等问题。     

基于加权FPN的聚驱综合调整系统决策分析

模糊Petri网(Fuzzy Petri Nets, FPN)是一种适合于描述异步并发事件的计算机系统模型,可以有效地对并行和并发系统进行形式化验证和决策分析.针对聚驱综合调整系统知识具有不确定性和模糊性的特点,给出了基于加权模糊产生式规则的加权FPN决策模型.在此模型的基础上,给出了决策推理过程的形式化推理算法.算法考虑了推理过程中的众多约束条件,将复杂的推理过程采用矩阵运算来实现,充分利用了FPN的并行处理能力,使决策推理过程更加简单和快速.并以压裂方式调整为例,说明了该模型具有直观、表达能力强和易于推理等优点,具有较强的实用价值.     

模糊推理Petri网及其在产品拆卸序列决策中的应用

为了在产品拆卸序列决策时,简化拆卸路径的分析难度,提出一种以模糊推理Petri网为工具的产品拆卸序列决策模型.采用将模糊推理Petri网与矩阵运算相结合的形式化推理算法,对所提出的决策算法进行了论述.实例应用结果表明,此模型在产品拆卸过程规划中具有很强的并行处理能力,可以根据产品在拆卸过程中零部件的最新信息对每一步操作作出适时的智能化决策,从而实现将产品中若干零件作为子装配体进行拆卸的自动聚类识别,减少了产品拆卸的复杂性.     

Modeling uncertainty reasoning with possibilistic Petri nets

Manipulation of perceptions is a remarkable human capability in a wide variety of physical and mental tasks under fuzzy or uncertain surroundings. Possibilistic reasoning can be treated as a mechanism that mimics human inference mechanisms with uncertain information. Petri nets are a graphical and mathematical modeling tool with powerful modeling and analytical ability. The focus of this paper is on the integration of Petri nets with possibilistic reasoning to reap the benefits of both formalisms. This integration leads to a possibilistic Petri nets model (PPN) with the following features. A possibilistic token carries information to describe an object and its corresponding possibility and necessity measures. Possibilistic transitions are classified into four types: inference transitions, duplication transitions, aggregation transitions, and aggregation-duplication transitions. A reasoning algorithm, based on possibilistic Petri nets, is also presented to improve the efficiency of possibilistic reasoning and an example related to diagnosis of cracks in reinforced concrete structures is used to illustrate the proposed approach.     

基于直觉模糊Petri网的故障诊断

故障诊断经常受到多种不确定性和模糊性因素的影响,针对不确定性的故障诊断问题,利用直觉模糊集较好的表达不确定性信息的优势和Petri网较好的并行处理以及图形处理问题的能力,构建了直觉模糊Petri网模型。由于将直觉模糊推理转化为矩阵运算的过程中有非隶属度参数的参与,因此推理结果可提供更多的信息。根据实际故障诊断中的模糊推理问题,给出了带有权值、阈值等参数条件下新的直觉模糊推理算法。通过获取和处理故障诊断中的不确定性和模糊性的知识,该算法将故障诊断过程转化为利用直觉模糊Petri网的直觉模糊推理过程。实际燃气轮机故障诊断模型案例表明了所给直觉模糊推理算法的有效性。     

模糊Petri网在带权不精确知识表示和推理中的应用研究

Petri网是一种适合于描述异步并发事件的计算机系统模型 ,可以有效地对并行和并发系统进行形式化验证和行为分析 .以模糊 Petri网的基本定义为基础 ,讨论了带权模糊知识的模糊产生式系统表示法 ,建立了这种表示法与模糊 Petri网之间的映射关系和转换算法 ;在对模糊 Petri网进一步扩充的基础上 ,解决了与知识的模糊Petri网表示相关的几个问题 ;最后给出了模糊 Petri网中不确定性的计算方法和相应的不精确推理算法     

模糊Petri网在航电总线系统故障诊断中的研究

航电总线系统结构复杂,各部件相互耦合,故障传播模式多样化。因此,为了处理故障诊断中不充分和模糊的信息,提出了将模糊Petri网应用到航电总线系统的故障诊断中,构建出其故障的传播模型,并在模型的基础上,给出有效的推理算法。表明利用模糊Petri网,可以建立航电总线系统的故障传播模式的模型,清晰地反映故障的产生、发展及影响。     

基于信息熵Petri网模型的知识发现研究

为描述命题和规则的可信度,定义了命题和规则的可信度信息熵。从熵的角度研究产生式规则中的不确定性推理,应用Petri网和可信度信息熵,建立了一类新的Information Entropy Petri网模型(IEPN),介绍了不确定性知识表示和推理步骤。同时分析IEPN推理对知识发现(KDD)的指导意义,并给出了IEPN推理过程及知识发现(KDK)方法。     

基于扩展模糊Petri网的知识推理方法研究

为使模糊Petri网能够描述可变模糊隶属判据下的模糊知识,利用基准变换能较好地表达模糊隶属判据可变情况的特点,基于定性映射和定性基准变换对模糊Petri网进行了扩展,给出了扩展后网模型的形式定义和基本运行机制。通过利用定性映射描述模糊产生式规则,给出了一种新的知识表示模式和推理方法,新方法有利于构建模糊Petri网基于认知的学习机制。结果显示,该网模型具有较强的知识表达能力,适用于处理认知模糊不确定性知识,其推理过程能体现某些认知特性,尤其适用于构建以定性判断为特点的智能系统。     

A fuzzy Petri net-based expert system and its application to damageassessment of bridges

In this paper, a fuzzy Petri net approach to modeling fuzzy rule-based reasoning is proposed to bring together the possibilistic entailment and the fuzzy reasoning to handle uncertain and imprecise information. The three key components in our fuzzy rule-based reasoning-fuzzy propositions, truth-qualified fuzzy rules, and truth-qualified fuzzy facts-can be formulated as fuzzy places, uncertain transitions, and uncertain fuzzy tokens, respectively. Four types of uncertain transitions-inference, aggregation, duplication, and aggregation-duplication transitions-are introduced to fulfil the mechanism of fuzzy rule-based reasoning. A framework of integrated expert systems based on our fuzzy Petri net, called fuzzy Petri net-based expert system (FPNES), is implemented in Java. Major features of FPNES include knowledge representation through the use of hierarchical fuzzy Petri nets, a reasoning mechanism based on fuzzy Petri nets, and transformation of modularized fuzzy rule bases into hierarchical fuzzy Petri nets. An application to the damage assessment of the Da-Shi bridge in Taiwan is used as an illustrative example of FPNES.     

A model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets

In many application areas there is a need to represent human-like knowledge related to spatio-temporal relations among multiple moving objects. This type of knowledge is usually imprecise, vague and fuzzy, while the reasoning about spatio-temporal relations is intuitive. In this paper we present a model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets. The model should be suitable for the design of a knowledge base for real-time, multi-agent-based intelligent systems that include expert or user human-like knowledge. The central part of the model is the knowledge representation scheme called FuSpaT, which supports the representation and reasoning for domains that include imprecise and fuzzy spatial, temporal and spatio-temporal relationships. The scheme is based on the high-level Petri nets called Petri nets with fuzzy spatio-temporal tokens (PeNeFuST). The FuSpaT scheme integrates the theory of the PeNeFuST and 117 spatio-temporal relations.The reasoning in the proposed model is a spatio-temporal data-driven process based on the dynamical properties of the scheme, i.e., the execution of the Petri nets with fuzzy spatio-temporal tokens. An illustrative example of the spatio-temporal reasoning for two agents in a simplified robot-soccer scene is given.     

模糊Petri网知识表示方法在入侵检测中的应用

根据网络攻击具有并发性,攻击特征的提取具有不确定性等特点,给出了采用模糊Pelri网实现攻击知识的表达和入侵检测的推理模型。该模型解决了误用入侵检测系统中现有知识表示方法不能并行推理的问题,以及传统的基于Pelri网可达图搜索求解导致模型描述复杂、推理缺少智能的问题。最后通过入侵实例验证了该模型的正确性和有效性。     

基于自学习模糊Petri网的知识化制造系统采购预测

对模糊Petri网进行改进,使其增加自学习能力,即自学习模糊Petri网(SFPN).提出了自学习模糊Petri网模型知识库的建立方法,通过构造SFPN模型知识库,建立并保存现有产品的SFPN模型,开发新产品或进行新的决策时调出并进行修正后作为新产品模型.通过较短时间和少量样本的自学习训练,便可用于新产品的预测或决策.最后通过采购预测实例验证了该方法的有效性.     

A reasoning algorithm for high-level fuzzy Petri nets

We introduce an automated procedure for extracting information from knowledge bases that contain fuzzy production rules. The knowledge bases considered here are modeled using the high-level fuzzy Petri nets proposed by the authors in the past. Extensions to the high-level fuzzy Petri net model are given to include the representation of partial sources of information. The case of rules with more than one variable in the consequent is also discussed. A reasoning algorithm based on the high-level fuzzy Petri net model is presented. The algorithm consists of the extraction of a subnet and an evaluation process. In the evaluation process, several fuzzy inference methods can be applied. The proposed algorithm is similar to another procedure suggested by Yager (1983), with advantages concerning the knowledge-base searching when gathering the relevant information to answer a particular kind of query     

Fuzzy rule base systems verification using high-level Petri nets

In this paper, we propose a Petri nets formalism for the verification of rule-based systems. Typical structural errors in a rule-based system are redundancy, inconsistency, incompleteness, and circularity. Since our verification is based on Petri nets and their incidence matrix, we need to transform rules into a Petri nets first, then derive an incidence matrix from the net. In order to let fuzzy rule-based systems detect above the structural errors, we are presenting a Petri-nets-based mechanism. This mechanism consists of three phases: rule normalization, rules transformation, and rule verification. Rules will be first normalized into Horn clauses, then transform the normalized rules into a high-level Petri net, and finally we verify these normalized rules. In addition, we are presenting our approach to simulate the truth conditions which still hold after a transition firing and negation in Petri nets for rule base modeling. In this paper, we refer to fuzzy rules as the rules with certainty factors, the degree of truth is computed in an algebraic form based on state equation which can be implemented in matrix computation in Petri nets. Therefore, the fuzzy reasoning problems can be transformed as the liner equation problems that can be solved in parallel. We have implemented a Petri nets tool to realize the mechanism presented fuzzy rules in this paper.     

基于模糊Petri网的汽车故障诊断仿真研究

本文将Petri网和模糊推理相结合,建立故障诊断的模糊Petri网模型。其中,用FPN表示模糊产生规则,用Petri网的变迁激活规则进行故障诊断推理,从而分析出异常行为过程间的因果关系,推理出故障的原因及其可信度。以汽车故障诊断为例,建立了基于模糊Petri网的诊断模型。通过仿真分析,验证了模型的正确性和算法的有效性。     

基于规则推理的FPN误用入侵检测方法

针对网络入侵攻击活动的模糊性，提出了一种基于模糊推理的模糊Petri网（FPN）误用入侵检测方法。该方法定义了一个六元组FPN，并将模糊产生式规则精化为两种基本类型。在此基础上给出了FPN表示模糊规则的模型、推理过程和基于FPN的推理算法。最后通过入侵检测的实例对该方法的正确性和有效性进行了验证，结果表明该方法推理过程简单直观、容易实现，而且具有并行推理能力，可适用于大规模的FPN模型，是误用入侵检测技术的一种非常有效的解决方案。