Intuitionistic Fuzzy Petri Nets Model Based on Back Propagation Algorithm for Information Services

Intuitionistic fuzzy Petri net is an important class of Petri nets,which can be used to model the knowledge base system based on intuitionistic fuzzy production rules.In order to solve the problem of poor self-learning ability of intuitionistic fuzzy systems,a new Petri net modeling method is proposed by introducing BP(Error Back Propagation)algorithm in neural networks.By judging whether the transition is ignited by continuous function,the intuitionistic fuzziness of classical BP algorithm is extended to the parameter learning and training,which makes Petri network have stronger generalization ability and adaptive function,and the reasoning result is more accurate and credible,which is useful for information services.Finally,a typical example is given to verify the effectiveness and superiority of the parameter optimization method.

A STUDY OF FUZZY LOGICAL PETRI NETS AND ITS APPLICATION

In this paper, a fuzzy Petri net approach to modelling fuzzy rule-based reasoning is proposed. Logical Petri net (LPN) and fuzzy logical Petri net (FLPN) are defined. The backward reasoning algorithm based on sub-fuzzy logical Petri net is given. It is simpler than the conventional algorithm of forward reasoning from initial propositions. An application to the partial fault model of a car engine in paper Portinale's(1993) is used as an illustrative example of FLPN.

Designing Genetic Regulatory Networks Using Fuzzy Petri Nets Approach

In this paper, we have successfully presented a fuzzy Petri net （FPN） model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition （HFT） to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network.

Method of Dynamic Knowledge Representation and Learning Based on Fuzzy Petri Nets

A method of knowledge representation and learning based on fuzzy Petri nets was designed. In this way the parameters of weights, threshold value and certainty factor in knowledge model can be adjusted dynamically. The advantages of knowledge representation based on production rules and neural networks were integrated into this method. Just as production knowledge representation, this method has clear structure and specific parameters meaning. In addition, it has learning and parallel reasoning ability as neural networks knowledge representation does. The result of simulation shows that the learning algorithm can converge, and the parameters of weights, threshold value and certainty factor can reach the ideal level after training.

Fuzzy reasoning model using fuzzy Petri Nets for the monitoring of robotic assembly

This paper presented a fuzzy Petri net model to deal with the monitoring of robotic assembly. Based on the fuzzy Petri net model, an efficient composite reasoning mode was proposed to perform fuzzy reasoning automatiealy. It can determine whether there exists an antecedent-consequence relationship between two contact states. Furthermore, various types of sensor signals can be converted to the same form of real values between zero and one, and the contradiction among large number, high degree of truth and importance of input conditions can be resolved very well by introducing the weight factors and priorities for sensor signals. Finally, a peg- in-the-hole example was given to illustrate the reasonability and feasibility of the proposed model.

基于模糊Petri网的引航员作业舒适度评价

为提高引航员的作业舒适度,提出一种基于模糊Petri网(FPN)的模糊推理算法(FRA)下的组合评价方法。首先,针对作业舒适度影响因子的不确定性信息,建立多因素耦合的FPN拓扑结构;然后,采用博弈论组合赋权法确定最优组合权重,提出融合层间相关性判断临界重要性、层次分析法和FRA,建立基于主客观权重的FRA,通过迭代求解库所可信度和状态矩阵;最后,结合上海港船舶引航的场景数据,基于FPN的FRA应用,评价引航员作业舒适度。结果表明:环境与引航设备是影响其作业舒适度的关键因素,冬季和夏季的引航作业舒适度评价等级对应“较不舒适”,其中,5月份为“较舒适”。所提方法充分体现系统舒适度影响因素的耦合特性。

一种分层模糊Petri网风险评估方法

针对传统模糊Petri网在对不确定环境下的专家系统的知识表示与推理时无法兼顾不确定知识的模糊性与随机性、在复杂的故障情况下故障的因果关系表达不清晰、定量推理计算时缺乏层次性、不能局部求解的问题,构建一种基于云模型的分层模糊Petri网以加强模糊Petri网的知识表示能力和提高推理过程的计算效率。利用专家知识和Petri网层次分解原则将系统故障模式和故障原因之间的因果关系进行建模,使故障建模更具结构性,计算更加灵活;应用云模型处理知识的模糊性和不确定性;通过合理考虑局部权重和全局权重,结合Petri网层次分解原则和云聚合算子给出相应的推理算法。实例验证表明,所提方法能够有效对系统进行风险评估,且在知识表示和推理方面优于其他方法。

融合PSO-模糊Petri网的室内燃气泄漏风险研究

近年来室内燃气事故多发,而燃气用户风险意识淡薄、户内安全检查难度大。针对现行室内燃气安全管理技术多为静态主观评估的局限性,构建了基于模糊Petri网(Fuzzy Petri Net,FPN)的风险计算规则,提出了结合粒子群优化算法(Particles Swarm Optimization,PSO)和FPN的室内燃气泄漏动态风险评估模型。首先,应用Petri网的直观图像描述和异步并发处理能力建立室内燃气泄漏事故风险演化的拓扑结构模型,借助FPN的模糊推理能力处理风险传播的不确定性;然后,根据燃气运维数据,融合PSO动态更新初始参数,提高风险评估的准确性。结果表明,基于PSO-FPN的室内风险评估方法可弱化燃气公司安检人员分析的主观不确定性,更为准确地量化风险因子演化过程,实现室内燃气泄漏风险的动态分析,有效支持户内燃气泄漏风险管控。

A FUZZY REASONING PETRI NET MODEL AND ITS REASONING ALGORITHM

This paper compared the difference between the traditional Petri nets and reasoning Petri nets(RPN),and presented a fuzzy reasoning Petri net(FRPN) model to represent the fuzzy production rules of a rule based system.Based on the FRPN model,a formal reasoning algorithm using the operators in max algebra was proposed to perform fuzzy reasoning automatically.The algorithm is consistent with the matrix equation expression method in the traditional Petri net.Its legitimacy and feasibility were testified through an example.

Dynamic properties of fuzzy Petri net model and related analysis

Fuzzy Petri net(FPN) has been extensively applied in industrial fields for knowledge-based systems or systems with uncertainty.Although the applications of FPN are known to be successful,the theoretical research of FPN is still at an initial stage.To pave a way for further study,this work explores related dynamic properties of FPN including reachability,boundedness,safeness,liveness and fairness.The whole methodology is divided into two phases.In the first phase,a comparison between elementary net system(EN_system) and FPN is established to prove that the FPN is an extensive formalism of Petri nets using a backwards-compatible extension method.Next,current research results of dynamic properties are utilized to analyze FPN model.The results illustrate that FPN model is bounded,safe,weak live and fair,and can support theoretical evidences for designing related decomposition algorithm.

Simulation Modeling by Fuzzy Nets

Fuzzy technology is a newly developed discipline based on fuzzy mathematics. In the recent years, it has been successfully applied into many areas, such as process control, diagnosis, evaluation, decision making and scheduling, especially in simulation where accurate mathematical models can not or very hard be established. In this paper, to meet the demands of fuzzy simulation, two fuzzy nets will first be presented, which are quite suitable for modeling the parallel or concurrent systems with fuzzy behavior. Then, a concept of active simulation will be introduced, in which the simulation model not only can show its fuzzy behavior, but also has a certain ability which can actively perform many very useful actions, such as automatic warning, realtime monitoring, simulation result checking, simulation model self-adapting, error recovery, simulating path tracing, system states inspecting and exception handling, by a unified approach while some specified events occur. The simulation model described by this powerful simulation modeling tool is concurrently driven by a network interpreter and an event monitor that all can be implemented by software or hardware. Besides, some interesting applications are given in the paper.

基于模糊Petri网和马尔科夫链理论的水电厂设备故障应急响应模型

为保证水电厂设备安全,避免因故障导致意外事故,基于模糊Petri网和马尔科夫链理论设计水电厂设备故障应急响应模型。确定加权因子命题阈值,结合传感器收集的初始信号,在滤波器的作用下还原信号特征,基于模糊Petri网提取水电厂设备故障特征。设计故障分类器,建立概率转移矩阵,设置概率转移矩阵的条件,面对动态解码,给定模型参数,计算马尔可夫模型下的连续变量密度函数,修正比例因子的状态系数,得到设备故障分类结果。建立设备故障应急响应模型,输出设备故障状态下的应急响应结果。实验结果显示,该模型在四种故障类型中的分类精度分别为98.8%、98.6%、98.7%、98.8%,可见该模型分类精度较好。

FINE-GRAINED DISTRIBUTED MULTIMEDIA SYNCHRONIZA-TION MODEL——ENHANCED FUZZY-TIMING PETRI NET

A fine grained distributed multimedia synchronization model——Enhanced Fuzzy timing Petri Net was proposed which is good at modeling indeterminacy and fuzzy. To satisfy the need of maximum tolerable jitter, the sufficient conditions are given in intra object synchronization. Method to find a proper granularity in inter object synchronization is also given to satisfy skew. Exceptions are detected and corrected as early as possible using restricted blocking method.

Arteriovenous Shunt Stenosis Evaluation Using a Fractional-Order Fuzzy Petri Net Based Screening System for Long-Term Hemodialysis Patients

This paper proposes the evaluation of arteriovenous shunt (AVS) stenosis using a fractional-order Fuzzy Petri net based screening system for long-term hemodialysis treatment of patients. The screening system uses the Burg method, the fractional-order chaos system, and the Fuzzy Petri net (FPN) for early detection of AVS dysfunction. The Burg method is an autoregressive (AR) model that is used to estimate the frequency spectra of a phonoangiographic signal and to identify the spectral peaks in the region from 25 Hz to 800 Hz. In AVS, the frequency spectrum varies between normal blood flow and turbulent flow. The power spectra demonstrate changes in frequency and amplitude as the degree of stenosis changes. A screening system combining fractional-order chaos system and FPN is used to track the differences in the frequency spectra between the normal and stenosis access. The dynamic errors are indexes that can be used to evaluate the degree of AVS stenosis using a FPN. For 42 long-term follow-up patients, testing results show that the proposed screening system is more efficient in the evaluation of AVS stenosis.

基于Fuzzy Petri网专家系统的研究

提出采用ＦｕｚｚｙＰｅｔｒｉ网作为知识表示和推理机制的模型，发挥其较好的模型描述和能处理并行推理的特点。基于ＦｕｚｙＰｅｔｒｉ网构造了一个耦合结构的专家数据库系统（ＥＤＢＳ），提高了推理的效率及其准确性，同时具有并发控制、数据组织、共享、存取和查询等数据库管理系统的功能，并使用投资决策实例对模型进行了解释和验证。

化工过程故障诊断的模糊概率Petri-net的研究

本文研究基于模糊与概率信息的模糊概率Petri net故障的诊断方法 ,概率信息用来解决问题冲突 ,模糊信息用来解决故障诊断不确定性并计算诊断的可靠性。在石油化工装置中的应用表明 。

基于改进的方向性加权模糊Petri网配电网故障诊断

为提高配电网保护动作信息丢失时故障诊断的准确率及容错性,提出了基于改进的方向性加权模糊Petri网配电网故障诊断方法。首先,考虑故障发生时近后备保护对可疑故障元件故障诊断的影响,对可疑故障元件的各个故障蔓延方向进行建模;其次,在专家经验的基础上采用随机数对模型输入权值进行随机赋值;最后,在保护动作信息丢失时,跟踪改变可疑故障元件保护未动作的可信度取值,并分析该故障诊断方法的适应性与容错性。仿真结果表明,所提基于改进的方向性加权模糊Petri网配电网故障诊断模型在信息不完备或者保护及断路器拒动时,均具有较高的故障诊断准确率。

基于NCM-FPN的古建筑修缮阶段施工安全综合评价

为有效预防古建筑修缮阶段施工安全事故,提出了基于正态云模型(Normal Cloud Model, NCM)与模糊Petri网(Fuzzy Petri Net, FPN)的施工安全综合评价方法。首先,分析古建筑修缮阶段施工特点及风险特性,建立多因素耦合作用下的三脚架事故致因模型(Tripod-Delta),构建指标体系。然后,将指标体系转换为施工安全多因素耦合FPN网络结构,采用NCM确定FPN指标初始状态,通过逆向搜索策略约简FPN冗余指标节点,并运用模糊推理算法与障碍因子诊断模型得出评价结果。结果表明,实例评价结果与现场情况基本一致,协同管理与材料设备是影响古建筑修缮阶段施工安全的关键因素。所提方法能充分表达古建筑修缮阶段施工安全风险的耦合特性,并确定安全管理的关键因素,评价结果客观准确。

基于模糊Petri网的配电变台工程成本偏差指标诊断与预警机制研究

大数据技术在配电网工程管理中的应用越来越广。当下,多数配电变台工程项目在数据处理方面能力有限,对需要重点管控的建设成本偏差指标的识别能力较弱,导致配电变台工程中长期存在的一些偏差指标难以得到及时地管控。设计基于模糊Petri网理论配电变台工程建设成本偏差指标的诊断模型及预警机制,并通过案例分析诊断出配电变台工程建设成本中须进行重点管控的偏差指标,预警后续可能会出现偏差的建设成本指标。所提出的诊断与预警方法可以为配电变台工程成本管理提供新思路。

基于物联网的加权模糊petri网电网故障诊断研究

为了解决电力SCADA系统监测数据存在漏报误报等情况造成故障诊断结果不可靠的问题,文章提出基于物联网的加权模糊petri网电网故障诊断方法。首先,考虑保护与断路器动作的逻辑顺序,对权值进行合理的设定;其次,对电网拓扑结构进行分析,建立故障元件按方向蔓延的加权模糊petri网模型;最后,将故障诊断结果与传感器网络监测到的温度数据相结合,分析故障诊断结果可信度的可靠性。仿真结果表明,所提出的基于物联网的加权模糊petri网电网故障诊断方法在监测中心获取信息不完备的情况下,仍可以得出正确的诊断结果,具有较高的适应性和容错性。