Fault prognosis of discrete event systems (DES) is an active field of research and has
become important due to the high demand on systems' safety and reliability. The aim of this …

Fuzzy Automaton plays a key role in modeling a system as a fuzzy discrete event system
and determining the model's properties such as observability and predictability. We recently …

We recently introduced a novel category of fuzzy discrete event systems (FDESs) termed
stochastic FDESs (SFDESs), wherein multiple fuzzy automata occur randomly with different …

The binary nature of the states and transitions in discrete-time finite Markov chains makes
this modeling methodology unsuitable for many practical systems, such as those found in …

This paper investigates the problem of reliable fuzzy prognosis of decentralized fuzzy
discrete event systems (FDESs) in face of possible unavailability of some local agents …

We recently proposed a new class of fuzzy discrete event systems called the stochastic fuzzy
discrete event systems (SFDES), which has the potential to be useful in a variety of …

Compared to other system modeling techniques, the fuzzy discrete event systems (FDESs)
methodology has the unique capability of modeling a class of event-driven systems as fuzzy …

We introduce a new class of fuzzy discrete event systems (FDESs) called stochastic FDESs
(SFDESs), which is significantly different from the probabilistic FDESs (PFDESs) in the …

Most of the published research on fuzzy discrete-event systems (FDESs) has focused on
systems that are modeled as deterministic fuzzy automata. In fact, nondeterminism in FDESs …

Recently, systems have become large in their model and dynamic. To apply control
algorithms, serious problems appear that need to be solved. Two significant problems are …