Results 251 to 260 of about 21,375,197 (296)

Abstract Petri Nets as a Uniform Approach to High-Level Petri Nets

1999
In the area of Petri nets, many different developments have taken place within the last 30 years, in academia as well as in practice. For an adequate use in practice, a coherent and application oriented combination of various types and techniques for Petri nets is necessary.
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On Formalizing UML with High-Level Petri Nets

2001
Object-oriented methodologies are increasingly used in software development. Despite the proposal of several formally based models, current object-oriented practice is still dominated by informal methodologies, like Booch, OMT, and UML. Unfortunately, the lack of dynamic semantics of such methodologies limits the possibility of early analysis of ...
BARESI, LUCIANO, PEZZE', MAURO
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Behaviour and Instantiation of High-Level Petri Net Processes

Fundamenta Informaticae, 2005
Processes for high-level nets are often defined as processes of the low-level net Flat(n) which is obtained from N via the well-known flattening construction. This low-level notion of processes for high-level nets, however, is not really adequate, because the high-level structure is completely lost.
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A high level Petri net model of olfactory bulb

IEEE International Conference on Neural Networks, 2002
A class of Petri nets (PNs), high level Petri nets (HPNs), are powerful and versatile tools for modeling, simulating, analyzing, designing and controlling complex asynchronous concurrent systems. An initial attempt is made to model biological neural networks (BNNs) with HPNs, since the interactions among neurons is basically asynchronous concurrent in ...
Kurapati Venkatesh, Oren Masory, Abhijit Pandya   +2 more
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A reasoning algorithm for high-level fuzzy Petri nets

IEEE Transactions on Fuzzy Systems, 1996
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 ...
Heloisa Scarpelli, Fernando A. C. Gomide, Ronald R. Yager   +2 more
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Algebraic high level nets

1994
Petri nets, well established as a fundamental model of concurrency and as a specification technique for distributed systems, are revisited from an algebraic point of view. In a first step Petri nets can be considered as monoids with well-defined algebraic semantics.
Hartmut Ehrig, Julia Padberg, Leila Ribeiro 0001   +2 more
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An object-oriented approach to High-Level Petri Nets

Microprocessing and Microprogramming, 1992
Abstract This paper introduces a class of High-Level Petri Nets, called τ-nets, used for the analysis, description, and sub-optimal solution of a general class of problems of process scheduling. τ-nets include timed transitions, a type-checking mechanism, and the definition of taxonomic hierarchies of token types.
Antonio Camurri, Paolo Franchi, Maurizio Vitale   +2 more
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Extending a net splitting operation for decomposition of high-level Petri nets

IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, 2012
This paper presents an extension to a net splitting operation for decomposition of high-level Petri nets, to support distributed implementations of embedded systems. The net splitting operation, selected from the survey of methods summarized in this paper, was originally proposed for low-level Petri nets.
Filipe Moutinho, Luís Gomes 0001
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Weak and Strong Composition of High-Level Petri Nets

1999
We propose generic schemes for basic composition operations (sequential composition, choice, iteration, and refinement) for high-level Petri nets. They tolerate liberal combinations of place types (equal, disjoint, intersecting) and allow for weak and strong versions of compositions (owing to a parameterised scheme of type construction).
Eike Best, Alexander Lavrov
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Reinforcement learning for high-level fuzzy petri nets

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2003
The author has developed a reinforcement learning algorithm for the high-level fuzzy Petri net (HLFPN) models in order to perform structure and parameter learning simultaneously. In addition to the HLFPN itself, the difference and similarity among a variety of subclasses concerning Petri nets are also discussed.
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