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According to CGF system, both of physical behavior model and intelligence decision-making model should be built. Under the background of ballistic missile countermeasure CGF decision-making system, this paper analysed the key factor that affect CGF decision-making. Secondly, it proposed a fuzzy Petri net(FPN) for CGF decision-making system modeling. Finally, it introduced a reasoning algorithm for fuzzy Petri net, which was used to analyze decision-making behavior of target choice for ballistic missile countermeasure. [ABSTRACT FROM AUTHOR]

Although a promising tool for knowledge representation and reasoning, fuzzy Petri nets (FPNs) still suffer from some deficiencies. First, the parameters in current FPN models, such as weight, threshold, and certainty factor do not accurately represent increasingly complex knowledge-based expert systems and do not capture the dynamic nature of fuzzy knowledge. Second, the fuzzy rules of most existing knowledge inference frameworks are static and cannot be adjusted dynamically according to variations of antecedent propositions. To address these problems, we present a new type of FPN model, dynamic adaptive fuzzy Petri nets, for knowledge representation and reasoning. We also propose a max-algebra based parallel reasoning algorithm so that the reasoning process can be implemented automatically. As illustrated by a numerical example, the proposed model can well represent the experts' diverse experience and can implement the knowledge reasoning dynamically. [ABSTRACT FROM AUTHOR]

Use of model gives the knowledge and information about the phenomenon also eradicates the cost, the effort and the hazard of using the real phenomenon. Characteristics and concepts of Petri nets are in a way that makes it simple and strong to describe and study the information processing system; especially it is shown in those which are dealing with discrete, concurrent, distributed, parallel and indecisive events. Yet, due to Petri nets inability to face with systems working on obscure data and continues events, the interest to develop fundamental concept of Petri nets has been raised which is led to new style of presented model named "fuzzy Petri nets". The difference in Petri nets is in the elements that have been fuzzed. Transitions, places, signs and arcs can be fuzzed. PMNL, on the other hand as a markup language has been engaged in uttering Petri nets in previous researches. Fuzzy markup nets can model the uncertainty of concurrent scenarios different from a dynamic system by a board of parameters and use of fuzzy membership dependencies. Therefore, in order to define these uncertain data, it is vital to use a formal language to describe fuzzy Petri nets. To support this version in this thesis, a markup language will be presented stating the structure and grammar of markup language and covering fuzzy concepts in Petri nets as well. Presenting the suggested grammar accommodates the support of fuzzy developed markup language and includes the combination of uncertainty and XML. [ABSTRACT FROM AUTHOR]

This paper presents a new class of Petri nets called generalised fuzzy Petri nets. The new class extends the existing fuzzy Petri nets by introducing three operators in the form of triangular norms, which are supposed to function as substitute for the min, max and * (algebraic product) operators. To demonstrate the power and the usefulness of this model, an application of the generalised fuzzy Petri nets in the domain of train traffic control is provided. The new model is more flexible than the classical one as in the former class the user has the chance to define the input/output operators. The proposed approach can be used for knowledge representation and reasoning in decision support systems. [ABSTRACT FROM AUTHOR]

In this document a methodological process is proposed, aimed to generate ladder diagrams from fuzzy Petri nets. The method is based on the "marks evolution analysis" concepts, which have been developed with the desire of implementing complex control systems expressed through fuzzy Petri nets, in programmable logical controllers (PLC). Furthermore the method is implemented using Matlab® as platform, getting a toolbox which allows: simulate the fuzzy Petri nets and generate the ladder diagram associated to that net. [ABSTRACT FROM AUTHOR]

Due to timing inconsistency, dual protection configuration and uncertainty diagnosis result characteristics of 750kV substation, fault diagnosis method of substation with redundant protection configuration which based on time sequence fuzzy Petri nets is proposed. In this method, redundant knowledge about fault component is represented by using two sets of protected information. On that basis, component redundant diagnosis-model based on time sequence fuzzy Petri net is constructed, which can be decomposed into main and redundant subnet-model. In this model, initial-information credibility is determined using information-entropy, timing constraint is checked, and initial-information credibility is corrected using the relationship between acted protection and breaker. Compared with fuzzy Petri net diagnosis method take no account of timing constraint, this method can not only identify the malfunction information, but also obtain a certain result. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to resolve the problem of complex system diagnosis with unobservable events such as Hall thruster. Design/methodology/approach – Fault class is defined by unobservable transitions subset. Every fault class is departed into four levels of alarm. The level of alarm for a fault class is identified by constructing basis reachability graph and computing j vector and basis marking. Certain factor values of diagnosis results are given by introducing two fuzzy operators. A two-directional reasoning strategy is adopted which are forward reasoning and backward reasoning. Findings – Using basis reachability graph and notions of basis marking and j vector, fuzzy Petri net with unobservable transitions can resolve the diagnosis problems with high accuracy and efficiency. Research limitations/implications – The relationship between unobservable events must be known. Practical implications – The method shows its superiority when it is applied to unobservable systems such as spacecraft. Originality/value – A novel fuzzy Petri net framework for unobservable system multi-fault diagnosis is put forward which introduces some new ideas. [ABSTRACT FROM AUTHOR]

In terms of the modeling needs of low-carbon manufacturing process for ceramic enterprises, the modeling method based on fuzzy Petri nets is introduced according to its basic principle and advantages that can grasp the continuity of the serving states and the impact of discrete states on continuous processes. Based on the analysis of the energy carbon-flow of the ceramic enterprises, the energy carbon-flow model of production process for ceramics is established based on generalized fuzzy Petri nets, and its formal definition and the rules explanation are given. Finally, taking firing system as an example, the model is used in ceramic enterprises to describe the dynamic behavior of energy carbon-flow and lay a theoretical foundation for low-carbon development. [ABSTRACT FROM AUTHOR]

Abstract: Even with the most accurate timetable, trains often operate with delays. The running and waiting times for trains can increase unexpectedly, creating primary delays that cause knock-on delays and delays for other trains. The accurate estimation of train delays is important for creating timetables, dispatching trains, and planning infrastructures. In this work, we proposed a fuzzy Petri net (FPN) model for estimating train delays. The FPN model with characteristics of hierarchy, colour, time, and fuzzy reasoning was used to simulate traffic processes and train movements in a railway system. The trains were coloured tokens, the track sections were termed places, and discrete events of train movement were termed transitions. The train primary delays were simulated by a fuzzy Petri net module in the model. The fuzzy logic system was incorporated in the FPN module in two ways. First, when there were no historical data on train delays, expert knowledge was used to define fuzzy sets and rules, transforming the expertise into a model to calculate train delays. Second, a model based on the Adaptive Network Fuzzy Inference System (ANFIS) was used for systems where the historical data on train delays were available (from detection systems or from the train dispatcher’s logs). The delay data were used to train the neuro-fuzzy ANFIS model. After the results of the fuzzy logic system were verified, the ANFIS model was replicated by a fuzzy Petri net. The simulation was validated by animating the train movement and plotting the time-distance graph of the trains. Results of the simulation were exported to a database for additional data mining and comparative analysis. The FPN model was tested on a part of the Belgrade railway node. [Copyright &y& Elsevier]

Abstract: For the purpose of understanding the students’ learning achievement, the most direct way is to implement a test. Due to the rapid development of information technology, all kinds of combination of information technology with the adaptive test have been incessantly noted by many scholars. In general, the computerized adaptive test includes the item response theory that tests the students’ learning ability of subjects. However, the results based only on the dichotomy of correct answers and wrong answers are not so comprehensive judgments. Situations of correct answers and wrong answers should be different in their degrees; for example, completely correct, partially correct, completely wrong, and partially wrong. But the partially correct or partially wrong is vague and difficult to define. Thus it is appropriate to use fuzzy theory to solve the vagueness problem. Therefore, this study presents a novel learning evaluation model which applies high-level fuzzy Petri net (HLFPN) and infers via a fuzzy reasoning method the different answering performances generated by different examinee’s abilities corresponding to the test items in different degrees of difficulty. Finally, we synthesize the answering performance of every test item and make a reasonable evaluation. [Copyright &y& Elsevier]

Using the concepts of network-centric control, we develop a design methodology for a controlling Petri net in real-time automation systems. The methodology involves the structured discrete-event system (SDES) model to analyze the functionality and coherence of the object. We define structure of the model, as well as propose a technique for analyzing and modeling the object via the process Petri net. Finally, we suggest an analysis technique for the process Petri net and develop a design method for a supervisor, i.e., a controlling Petri net which implements the SDES specification (in coherence with the process net). [ABSTRACT FROM AUTHOR]

For the sake of strengthening knowledge representation of fuzzy Petri nets, attributes fuzzy Petri nets (AFPN) are presented. On the basis of fuzzy Petri nets, places and weights are endowed with attributes which are related to actual system, so that the AFPN model of multiple attributes system is of simple model structure. AFPN models are stored in knowledge base of knowledgeable manufacturing systems, and irregular models are regularized after attributes decomposing, attributes merging, and model training. Thus, a new products processing AFPN model can be established simply and fast on the basis of original AFPN model. In the examples of products demand forecasting, demand forecasting AFPN model is established by using demand-related data of products and materials, and it can forecast products demands quickly. [ABSTRACT FROM AUTHOR]

Product ecosystem design entails complex user experience (UX) that involves interactions among multiple users, products, and the ambience. This paper aims to capture causal relationships between UX and design elements and in turn to provide decision support to product ecosystem analysis. A fuzzy reasoning Petri net is developed to deal with the uncertainty, complexity, and dynamics associated with UX modeling. Reasoning of diverse constructs of UX is embedded in the fuzzy production rules that are derived from self-report UX data based on rough set mining. A fuzzy reasoning algorithm is implemented to perform parallel inference by multicriteria rules and to simulate most likely UX under different ambient factors. A case study of subway station UX design demonstrates the potential of product ecosystem FRPN formulation. [ABSTRACT FROM PUBLISHER]

Unlike other techniques, Li and Zhou add control nodes and arcs for only elementary siphons greatly reducing the number of control nodes and arcs (implemented by costly hardware of I/O devices and memory) required for deadlock control in Petri net supervisors. Li and Zhou propose that the number of elementary siphons is linear to the size of the net. An elementary siphon can be synthesized from a resource circuit consisting of a set of connected segments. We show that the total number of elementary siphons, ПE, is upper bounded by the total number of resource places PR lower than that min(P, T) by Li and Zhou where P (T) is the number of places (transitions) in the net. Also, we claim that the number of elementary siphons ПE equals that of independent segments (simple paths) in the resource subnet of an S3PR (systems of simple sequential processes with resources). Resource circuits for the elementary siphons can be traced out based on a graph-traversal algorithm. During the traversal process, we can also identify independent segments (i.e. their characteristic T-vectors are independent) along with those segments for elementary siphons. This offers us an alternative and yet deeper understanding of the computation of elementary siphons. Also, it allows us to adapt the algorithm to compute elementary siphons in [2] for a subclass of S3PR (called S4PR) to more complicated S3PR that contains weakly dependent siphons. [ABSTRACT FROM AUTHOR]

Abstract: To address the impact of solar array anomalies, it is important to perform analysis of the solar array reliability. This paper establishes the fault tree analysis (FTA) and fuzzy reasoning Petri net (FRPN) models of a solar array mechanical system and analyzes reliability to find mechanisms of the solar array fault. The index final truth degree (FTD) and cosine matching function (CMF) are employed to resolve the issue of how to evaluate the importance and influence of different faults. So an improvement reliability analysis method is developed by means of the sorting of FTD and CMF. An example is analyzed using the proposed method. The analysis results show that harsh thermal environment and impact caused by particles in space are the most vital causes of the solar array fault. Furthermore, other fault modes and the corresponding improvement methods are discussed. The results reported in this paper could be useful for the spacecraft designers, particularly, in the process of redesigning the solar array and scheduling its reliability growth plan. [Copyright &y& Elsevier]

Abstract: Temperature control systems have the characteristics of non-linearity, large inertia, and time variance. It is difficult to overcome the effects of these factors and get a reasonable results with the use of conventional controllers such as PID. So, temperature control by a robust neural fuzzy Petri net (RNFPN) controller based on an indirect forward control structure is proposed in this paper. After offline learning to get the initial weights, the RNFPN is online constructed by concurrent structure/parameter learning. The RNFPN has many advantages when applied to temperature control plants such as: high learning ability which reduces the controller training time, no a priori knowledge of the plant is required which simplifies the design task, and lastly the high control performance. The simulation results showed that the RNFPN intelligent controller has a reasonable robustness against disturbance, rapidity and good dynamic performance. [Copyright &y& Elsevier]

Abstract: Exception handling plays a key role in dynamic workflow management that enables streamlined business processes. Handling application-specific exceptions is a knowledge-intensive process involving different decision-making strategies and a variety of knowledge, especially much fuzzy knowledge. Current efforts in workflow exception management are not adequate to support the knowledge-based exception handling. This paper proposes a hybrid exception handling approach based on two extended knowledge models, i.e., generalized fuzzy event–condition–action (GFECA) rule and typed fuzzy Petri net extended by process knowledge (TFPN-PK). The approach realizes integrated representation and reasoning of fuzzy and non-fuzzy knowledge as well as specific application domain knowledge and workflow process knowledge. In addition, it supports two handling strategies, i.e., direct decision and analysis-based decision, during exception management. The approach fills in the gaps in existing related researches, i.e., only providing the capability of direct exception handling and neglecting fuzzy knowledge. Based on TFPN-PK, a weighted fuzzy reasoning algorithm is designed to address the reasoning problem of uncertain goal propositions and known goal concepts by combining forward reasoning with backward reasoning and therefore to facilitate cause analysis and handling of workflow exceptions. A prototype system is developed to implement the proposed approach. [Copyright &y& Elsevier]

A couple of experiments were carried out to investigate the effects of osmopriming and hydropriming treatments on the germination indexes and seed vigor of Tall fescue (Festuca arundinacea). In the first experiment, fulfilled based on randomized complete block designed with four replicates, the effect of polyethyleneglycol 6000 solution with five osmotic potentials (-8, -10, -12, -14 and -16 bar), two temperatures (15 and 25°C) and four time intervals (12, 24, 36 and 48 hours) was analized. The second experiment was fulfilled by using distilled water at two temperatures (15 and 25°C) and four time intervals (12, 24, 36 and 48 hours) with four replicates on the above mentioned data. Then, based on the maximum germination rate and vigor indexes, the optimal treatment composition was determined for osmopriming and hydropriming solutions in regard to the osmotic potential, temperature and priming duration. In osmopriming experiment, treatment composition of 12 hours at 15°C and -8 bar had the most significant effect on the percent and speed of germination, length of radicle, coleoptile and seedling, as well as vigor indexes in Tall fescue. For hydropriming, the effect analyzed in the same condition as osmopriming, was observed in the majority of evaluated traits; treatment composition of 12 hours prime and 15°C had the maximum numerical value in comparison to control and other treatments. Finally, it is inferred that favorable effects of osmoand hydropriming at 15°C temperature are more significant in comparison with the control group (none prime seeds). [ABSTRACT FROM AUTHOR]

This study focuses on the design of robust path tracking control for a mobile robot via a dynamic Petri recurrent fuzzy neural network (DPRFNN). In the DPRFNN, the concept of a Petri net (PN) and the recurrent frame of internal feedback loops are incorporated into a traditional fuzzy neural network (FNN) to alleviate the computation burden of parameter learning and to enhance the dynamic mapping of network ability. This five-layer DPRFNN is utilized for the major role in the proposed control scheme, and the corresponding adaptation laws of network parameters are established in the sense of projection algorithm and Lyapunov stability theorem to ensure the network convergence as well as stable control performance without the requirement of detailed system information and the compensation of auxiliary controllers. In addition, the effectiveness of the proposed robust DPRFNN control scheme is verified by experimental results of a differential-driving mobile robot under different moving paths and the occurrence of uncertainties, and its superiority is indicated in comparison with a stabilizing control system. [ABSTRACT FROM AUTHOR]

A reliable energy-efficient multi-level routing algorithm in wireless sensor networks is proposed. The proposed algorithm considers the residual energy, number of the neighbors and centrality of each node for cluster formation, which is critical for well-balanced energy dissipation of the network. In the algorithm, a knowledge-based inference approach using fuzzy Petri nets is employed to select cluster heads, and then the fuzzy reasoning mechanism is used to compute the degree of reliability in the route sprouting tree from cluster heads to the base station. Finally, the most reliable route among the cluster heads can be constructed. The algorithm not only balances the energy load of each node but also provides global reliability for the whole network. Simulation results demonstrate that the proposed algorithm effectively prolongs the network lifetime and reduces the energy consumption. [ABSTRACT FROM AUTHOR]

Although much progress has been made in developing seat belts and mandating their use, the injuries related to seat belts during frontal crashes are still widespread. This paper proposes an approach to control the seat belt restraint system force during a frontal crash to reduce thoracic injuries. A fuzzy logic controller based on moving the attachment point of the seat belt is proposed, and the simulation results with this controller are presented. Also, robustness to parameter variations is investigated. The results show that the proposed controller is very effective in reducing all critical values that lead to possible thoracic injuries during a frontal crash. The controller is also demonstrated to be robust with respect to varying impact conditions and parameters. [ABSTRACT FROM AUTHOR]

We introduce the concepts of fuzzy Petri nets and marked fuzzy Petri nets along with their appropriate morphisms, which leads to two categories of such Petri nets. Some aspects of the internal structures of these categories are then explored, for example, their reflectiveness/coreflectiveness and symmetrical monoidal closed structure. [ABSTRACT FROM AUTHOR]

Motivated by Zadeh's paradigm of computing with words (CWs) rather than numbers, several formal models of CWs have recently been proposed. These models are based on automata and, thus, are not well suited for concurrent computing. In this paper, we incorporate the well-known model of concurrent computing, which is called the Petri net, together with fuzzy-set theory and, thereby, establish a concurrency model of CWs--fuzzy Petri nets for CWs (FPNCWs). The new feature of such fuzzy Petri nets is that the labels of transitions are some special words modeled by fuzzy sets. By employing the methodology of fuzzy reasoning, we give a faithful extension of an FPNCW that makes computing with more words possible. The language expressiveness of the two formal models of CWs, i.e., fuzzy automata for CWs as well as FPNCWs, is compared. A few small examples are provided to illustrate the theoretical development. [ABSTRACT FROM AUTHOR]

With the increase in the number senior citizens and chronic diseases, the number of elderly patients who need constant assistance has increased. One key point of all critical care for elderly patient is the continuous monitoring of their vital signs. Among these, the ECG signal is used for noninvasive diagnosis of cardiovascular diseases. Also, there is a pressing need to have a proper system in place for patient identification. Errors in patient identification, and hence improper administration of medication can lead to disastrous results. This paper proposes a novel embedded mobile ECG reasoning system that integrates ECG signal reasoning and RF identification together to monitor an elderly patient. As a result, our proposed method has a good accuracy in heart beat recognition, and enables continuous monitoring and identification of the elderly patient when alone. Moreover, in order to examine and validate our proposed system, we propose a managerial research model to test whether it can be implemented in a medical organization. The results prove that the mobility, usability, and performance of our proposed system have impacts on the user's attitude, and there is a significant positive relation between the user's attitude and the intent to use our proposed system. [ABSTRACT FROM AUTHOR]

Abstract: Multicast routing protocols need a new path discovery algorithm for a newly joining node (receiver) in an ad hoc network. One issue of the approach to find the nearest forwarding node for a new node is that it may increase the distance between the source node and the new members, which results in an increase in latency time and packet loss, as compared with the shortest path algorithms. This issue is important in a high collision network. In this paper, we propose a knowledge-based inference approach for a new path discovery for multicasting. A fuzzy Petri net agent, which is a special expert system, is introduced at each node to learn and to adjust itself to fit the dynamic conditions in a multicast ad hoc network. The simulation results show that the proposed approach is up to 67.17% more efficient in the packet delivery ratio as compared with a bandwidth effective multicast routing protocol. [Copyright &y& Elsevier]

Abstract: Railway traffic control by dispatchers in case of abnormality is critical to assure the service quality of a railway system’s operation. However, this unique professional knowledge often lies in the dispatcher’s mind. Therefore, this study aims to transform a train dispatcher’s expertise into a useful knowledge rule. The fuzzy Petri Net approach is adopted to formulate the decision rules of train dispatchers in case of abnormality as the basis for future development of a dispatching decision support system. The dispatching decision rules, factors, and possible options when perturbation happens are collected via expert interviews and literature reviews. This study discusses the abnormal scenarios, including centralized traffic control system failure, automatic train protection failure, and locomotive failure. A case study of a line section of Taiwan’s railway network is implemented and the empirical result could be used as a reference in railway dispatching in case of abnormality. [Copyright &y& Elsevier]

As product lifecycles are getting shorter and shorter, manufacturers are facing a great deal of economic and political pressure to reclaim and recycle their obsolete products. Disassembly, as one of the natural solutions, is of increasing importance in material and product recovery. However, this process is fraught with a high level of uncertainty (e.g., variations in product structure and condition, and human factors). The development of an effective modeling and management tool for such involved factors is critical in moving disassembly toward a more efficient and automated regime. This paper builds upon our previous work to undertake this problem. More specifically, a fuzzy Petri net model is introduced to explicitly represent the dynamics inherent in disassembly. Instead of presuming the pertinent data in the model is already known, a self-adaptive disassembly process planner and associated computationally effective algorithms are designed in a way to: 1) accumulate the past experience of predicting such data and, at the same time, 2) exploit the "knowledge" captured in the data to choose the best disassembly plan and improve the overall disassembly performance. To ensure the robustness of the learning procedure, variable memory length is further introduced. The proposed methodology and algorithms are illustrated through the disassembly of a batch of personal computers in a prototypical disassembly system. [ABSTRACT FROM AUTHOR]

This paper designs a class of Fuzzy Petri net controller based on the character of place invariant in Petri net. This controller is simple in operation and is easy to put into practice. It has satisfying effects and can provide methods to do research in designing and optimizing the performance of system in solving the dead lock phenomenon in concurrent system. [ABSTRACT FROM AUTHOR]

Event sequences estimation is an important issue for fault diagnosis of Discrete event systems, so far as fault events cannot directly be measured. This paper is about event sequences estimation with Petri net models. Events are assumed to be represented with transitions, and firing sequences are estimated from measurements of the marking variation. Estimation with and without measurement errors are discussed in n-dimensional vector space over alphabet Z3 = { -1, 0, 1 }. Sufficient conditions and estimation algorithms are provided. Performance is evaluated, and the efficiency of the approach is illustrated on two examples from manufacturing engineering. [ABSTRACT FROM AUTHOR]

State of the art information system commonly record events in log files, also known as audit trails. Moreover, business processes often go beyond the sole recording the events and base decisions on the events observed in the past. To model such processes we extend the basic Petri net framework with the notion of history by associating tokens with histories, adding guards evaluated on the history to the transitions and mapping arcs to expressions involving histories. Guards and arc expressions can involve data associated with the transitions. [ABSTRACT FROM AUTHOR]

We propose a trace-based approach to description behaviours of concurrent systems. First, we define the independency relation induced by arbitrary transition system, forming this way an asynchronous transition system. Then we introduce the notion of traceability of transition systems and study some decision problems, related to computing independency and deciding traceability for basic classes of Petri nets. Main results: traceability is decidable for place/transition nets and undecidable in broader classes of nets – inhibitor, reset and transfer nets. [ABSTRACT FROM AUTHOR]

Modern knowledge representation is a very dynamic domain because of continuous research and development. This paper presents Logical Petri Nets (LPNs) and Fuzzy Petri Nets (FPNs) as models for knowledge representation. It is shown that knowledge propagation, described using logical and fuzzy Petri nets, terminates in a unique stable state. Based on this result, the paper introduces an algorithm for knowledge propagation in decision support systems. [ABSTRACT FROM AUTHOR]

In an aiming system it is hard to show dynamic behaviors in fault diagnosis. Fuzzy Petri net is applied to the method of modeling fault transmission. Fuzzy production rules are introduced into knowledge representation, and the fault diagnosis method using fuzzy Petri net and its reasoning algorithm are discussed. Using this method in fault diagnosis in an aiming system, the result demonstrates that fuzzy Petri net has an easy structure, a good expression of faults and effective capability of fuzzy reasoning. Fuzzy Petri net is a useful method in fault diagnosis. [ABSTRACT FROM AUTHOR]

The concept of an intellectual logistical network (ILN) for modeling transformed circuits is proposed. The ways of the description of ILN by Petri nets are considered. Management of such network is carried out on the basis of principles of behavior of artificial alive essences - animates, in particular self-training. With the purpose of reduction of amount of possible initial marks of model, the algorithm of calculation of "expedient" set of initial marks is offered. The way to "reasonable" changing of a network is proposed also. [ABSTRACT FROM AUTHOR]

Fuzzy reasoning Petri-nets (PN5) is a promising technique to tackle the complexities of power system fault section estimation. This paper addresses several key issues in implementing Fuzzy reasoning PNs for fault section estimation, which include optimal design of structure of diagnosis models to avoid large matrix size, utilization of fuzzy logic parameters to effectively handle uncertainties, realization of matrix execution algorithm to achieve parallel reasoning and adaptability, and integration of more reliable input data to enhance estimation accuracy. Case studies are presented to demonstrate the estimation capability under complex scenarios. An implementation solution residing in a control center is proposed. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this work is to propose an approach based on a p-time Petri net model with hybrid resources to solve the real time scheduling problem of Workflow Management Systems. The proposed approach uses an activity diagram to show the main activities of the system and the different routings of the Workflow Process. Based on the activity diagram, the corresponding p-time Petri net model is produced by assigning a time interval to every Workflow activity. Hybrid resource (discrete+continuous) allocation mechanisms are modeled by an hybrid Petri net with discrete transitions in order to represent the different kinds of resources (equipment and human resources) in a more realistic way. Time constraint propagation mechanisms are presented and a token player algorithm is applied to the Petri net model in order to obtain an acceptable scenario corresponding to a specific sequence of activities which respects the time constraints. The approach is illustrated through an example of “Handle Complaint Process”. [Copyright &y& Elsevier]

In this paper, we propose Self-Adapting Recovery Net (SARN), an extended Petri net model, for specifying exceptional behavior in business processes. SARN adapts the structure of the underlying Petri net at run time to handle exceptions while keeping the Petri net design easy. The proposed framework caters for the specification of high-level recovery policies that are incorporated either with a single task or a set of tasks, called a Recovery Region. These recovery policies are generic directives that model exceptions at design time together with a set of primitive operations used at run time to handle the occurrence of exceptions. We identified a set of recovery policies that are useful .and commonly needed in many practical situations. A tool has been developed to illustrate the viability of the proposed exception handling technique. [ABSTRACT FROM AUTHOR]

In an industrial decentralization context of control and migration of intelligence downwards, mechanical equipments with more and more electronics and automations have been developed given the so called mechatronic systems. However this rapid progression of new technology has contributed to increase the systems complexity and decrease the mastering. The industrial diagnosis associated at a precocious detection of degradations have a key role in quality mastering, availability improve and productivity of the production tool. The industrial diagnosis methods are divided in two categories: diagnosis methods with formal model of the equipment and diagnosis methods without equipment model. The formal mathematical models of industrial equipments are often with uncertainties and difficult to built. This paper proposes a method based explanatory model which is best suited to model the cause-effect relationships essential for the industrial diagnosis. We adapt a novel tool of assistance to diagnosis based on the fuzzy Petri nets (FPN). An industrial application concludes this work. [ABSTRACT FROM AUTHOR]

The application of fuzzy Petri Nets (FPN5) to the development of intelligent systems has received increasing attention recently. However, the fuzzy production rules are rather limited if the determination of certainty factor for each proposition is subjective. Unfortunately, this is the case for many existing FPNs. This paper proposes a generalized associative Petri net (APN) model with associative degree and knowledge representation of a rule-based system. Based on the generalized APN model, an efficient reasoning algorithm is proposed. The ontology mapping and the associative reasoning algorithm are described formally in details. An example of malicious e-mail reasoning is also included as an illustration. [ABSTRACT FROM AUTHOR]

In this article I will prove undecidability results for elementary object net systems (EOS). Object nets are Petri nets which have Petri nets as tokens – an approach which is called the "netswithin-nets" paradigm. EOS are special object net systems which have a two leveled structure. [ABSTRACT FROM AUTHOR]

Knowledge intensive applications require an intelligent environment, which can perform deductions in response to user queries or events that occur inside or outside of the applications. For that, we propose a fuzzy Petri net (FPN) model to represent knowledge and the behavior of an intelligent object-oriented database environment, which integrates fuzzy, active and deductive rules with database objects. The behavior of a system can be unpredictable due to the rules triggering or untriggering each other (non-termination). Intermediate and final database states may also differ according to the order of rule executions (non-confluence). In order to foresee and solve problematic behavior patterns, we employ a static rule analysis on the FPN structure that provides easy checking of the termination property without requiring any extra construct. In addition, with our proposed fuzzy inference algorithm, we guarantee confluent rule executions. The techniques and solutions provided in this study can be used in various complex systems, such as weather forecasting applications, environmental information systems, defense applications. [Copyright &y& Elsevier]

Many construction markets exhibit severe price competition where contractors have to cut their bids to compete, giving priority to winning enough contracts to sustain normal operation, and it is common to see a winning bid close to the expected project cost. While cutting bids not only gives up profits but also undoubtedly increases the risk of making a loss, the behavior of contractors in intense competition is difficult to explain by existing models. A fuzzy-logic-based model is proposed for determining the minimum bid markup with assessments of chance of winning and loss risk. The model incorporates the position of a decision maker in the fuzzy rules according to his/her attitude toward risk and degree of need for the job. Two illustrative examples, one hypothetical and one real, are provided, in which differences in priorities are simulated by four sets of fuzzy rules for a comparison of the effects. The results show that the model is sensitive enough to differentiate a decision maker's position on bidding and suggest bid-cutting limits consistently, thereby remedying some shortcomings of existing models. [ABSTRACT FROM AUTHOR]

Diagnosing multiple faults that may occur in distributed systems has received a lot of attention over the last decade. In particular, a backward reachability analysis based on Behavioral Petri Net (BPN) models has been proposed to model-based diagnosis of such systems. Nevertheless, it has been defined without tacking into account the concept of precedence relationships that may exist among fault indications or symptoms. The aim of this paper is two fold: first, to extend such analysis to handle precedence orders among symptoms at their signalization time; and second, to deal with the problem of contradictory observations which conduct to an inconsistency in the given problem. The relationships among symptoms are expressed in the net model as transitions among places denoting the corresponding symptoms. For the diagnosis process, they are captured through a novel set of backward firing rules used to construct the corresponding marking graph. In order to treat the inconsistency problems, we propose to restore the required consistency to the given problem. This is accomplished by identifying some symptoms that are known to be absent in the case under examination and when they are supposed present will explain the observed misbehavior. The paper is written in an informal style emphasizing on considerations of practical order than theoretical ones. [ABSTRACT FROM AUTHOR]

Supervisory control theory is well developed, but its use in industrial applications can be limited by a set of problems arising when supervisors have to be implemented on common control machines. As a matter of fact, the asynchronous and undetermined nature of supervisors makes their implementation on synchronous devices like programmable logic controllers (PLCs) and PCs a complicated task. In this paper, an overview on the existing techniques about this topic is given first. Then, the supervised control approach is used to implement supervisors and the supervised control architecture consisting of a controller and a supervisor is completed by a dispatcher to obtain a closed-loop, determined behavior. The main problems occurring in implementing supervised control on synchronous devices are presented and discussed. Finally, a method is proposed to translate automata, Petri Net or colored Petri Net supervisors in structured text language, one of the IEC 61131-3 standard languages, by preserving their structure and the closed-loop behavior as expected from the theory. [ABSTRACT FROM AUTHOR]