This paper handles the problem of uncertainty in assessment the safety systems using Generalized Stochastic Petri Nets (GSPN). The basic probabilities usually treated to define transition in petri nets (PNs) are substituted by fuzzy number. Experts represent the uncertainties regarding the parameters of the components of systems to assess the influence of this uncertainty on safety system unava...

In the first part of this paper we extend the semantical framework proposed in [22] for process and causality semantics of Petri nets by an additional aim, firstly mentioned in the habilitation thesis [15]. The aim states that causality semantics deduced from process nets should be complete w.r.t. step semantics of a Petri net in the sense that each causality structure which is enabled w.r.t. s...

Task assignment processes and its control implying reasoning about objects and resources and their changing states are dominated by discrete or stochastic-event dynamics or both. Estimating the components position of the mobile robot provided by sensor generates unknown, hidden variables which will be model by the means of probabilistic inference taking into account incomplete and uncertain inf...

After some general considerations concerning modeling issues , the paper concentrates on the fact that places are generally interpreted as logical conditions. There are various kind of logical propositions , some (the resources) are consumed when they are used in the same way tokens are removed from places when transitions are red. Linear logic has pointed out the fact that resources had to be ...

The paper presents a Petri net infrastructure that should allow sharing Petri nets on the Semantic Web. Previous solutions only provide model interchange mechanisms between Petri net tools. The Petri net ontology is a central part of our solution. The ontology is closely related to the Petri Net Markup Language (PNML) – an ongoing Petri net community sharing effort. We developed the Petri net o...

New Neuro-Fuzzy Systems, using algorithms for unsupervised fuzzy clustering based on so-called Weighted Neural Networks, are introduced and used for Unsupervised Image Segmentation. New incremental and fixed (or grid-partitioned) Weighted Neural Networks (WNN) are introduced and used for this purpose. The WNN algorithm (incremental or grid-partitioned) produces a net, of nodes connected by edge...