A Petri net is an abstract formal model of the behavior of a system and information flow. The properties, concepts, and techniques of Petri net are so as to present it as a simple and strong method for describing and analyzing information flow and systems control. Fuzzy Petri Net (FPN) is an appropriate powerful model to emulate knowledge base systems using fuzzy rules. Yet, FPN model does not ...

Due to high nonlinearities and time-varying dynamics of today’s control systems fuzzy learning controllers find appliance in practice. The present paper proposes a method for the synthesis of the learning fuzzy controllers where an expert knowledge about a process is applied to form a learning mechanism that is used to acquire information for the knowledge base of the main fuzzy controller. Acc...

In most Fuzzy System applications the structure of the system is chosen non-systematically by an expert according to his knowledge. Nevertheless the system parameters are rich enough to ensure the desired behavior. In the following, we introduce an automatic learning algorithm by de nition of a 1) well behaved and 2) minimal Fuzzy System. A Genetic Algorithm is used to estimate the Fuzzy System...

Fault diagnosis is a vital discussion in power systems restoration. Recently, much research endeavors have been done for fault section diagnosis of power systems by using several techniques, such as rule-based expert system, logic-based expert system, fuzzy relation based expert system, neural network, optimization techniques based approach, etc. They diagnose the fault from different ways. How...

Organizations rely on security experts to improve the security of their systems. These professionals use background knowledge and experience to align known threats and vulnerabilities before selecting mitigation options. The substantial depth of expertise in any one area (e.g., databases, networks, operating systems) precludes the possibility that an expert would have complete knowledge about a...

It is introduced an approach to the problem of "building logics" over sets of facts with only structured by a fuzzy relation of "consequence". Notions of "Truth" and "Falsehood" are introduced by means of two generalizations for classical Modus Ponens and Modus Tollens. Studying this concepts a theoretical base to explain the mode of reasoning in expert systems is obtained. By studying fuzzy tr...

According to the traditional control methods of batching-material exists system defects low precision and bad real time, this paper has proposed the combined control algorithm. This paper has designed a Fuzzy-PID control Glass batching-material system by using of combining the traditional PID and the Fuzzy control algorithm. The system uses expert system of online learning and adjusts automatic...

The practice, common in fuzzy expert systems, to map linguistic data into fuzzy sets has some important reverse implications: given membership functions that represent different terms of a linguistic variable in one natural language , we can set out to search which of them best matches a given term in another language , on the basis of similarity assessments between individual terms. In other w...

We briefly describe the medical expert system Cadiag-2, developed to support the differential diagnostic process in internal medicine. We propose a propositional logic called fuzzy probability logic as a possible formalization of Cadiag-2 and indicate the way of transferring Cadiag-2's methodology into this framework.

This paper provides a framework for integrating fuzzy expert systems with discrete event simulation, which will be utilized to enhance the input modeling process in discrete event simulation. Predicting the activity output (i.e. duration) using fuzzy expert systems will provide a new modeling feature to discrete event simulation. In previous studies, fuzzy set theory was mainly utilized to cont...