289,656 research outputs found
Discrete event simulation tool for analysis of qualitative models of continuous processing systems
An artificial intelligence design and qualitative modeling tool is disclosed for creating computer models and simulating continuous activities, functions, and/or behavior using developed discrete event techniques. Conveniently, the tool is organized in four modules: library design module, model construction module, simulation module, and experimentation and analysis. The library design module supports the building of library knowledge including component classes and elements pertinent to a particular domain of continuous activities, functions, and behavior being modeled. The continuous behavior is defined discretely with respect to invocation statements, effect statements, and time delays. The functionality of the components is defined in terms of variable cluster instances, independent processes, and modes, further defined in terms of mode transition processes and mode dependent processes. Model construction utilizes the hierarchy of libraries and connects them with appropriate relations. The simulation executes a specialized initialization routine and executes events in a manner that includes selective inherency of characteristics through a time and event schema until the event queue in the simulator is emptied. The experimentation and analysis module supports analysis through the generation of appropriate log files and graphics developments and includes the ability of log file comparisons
Conflict-driven Hybrid Observer-based Anomaly Detection
This paper presents an anomaly detection method using a hybrid observer --
which consists of a discrete state observer and a continuous state observer. We
focus our attention on anomalies caused by intelligent attacks, which may
bypass existing anomaly detection methods because neither the event sequence
nor the observed residuals appear to be anomalous. Based on the relation
between the continuous and discrete variables, we define three conflict types
and give the conditions under which the detection of the anomalies is
guaranteed. We call this method conflict-driven anomaly detection. The
effectiveness of this method is demonstrated mathematically and illustrated on
a Train-Gate (TG) system
Modular nonblocking verification using conflict equivalence
This paper proposes a modular approach to verifying
whether a large discrete event system is nonconflicting.
The new approach avoids computing the synchronous
product of a large set of finite-state machines. Instead, the
synchronous product is computed gradually, and intermediate
results are simplified using conflict-preserving abstractions
based on process-algebraic results about fair testing. Heuristics
are used to choose between different possible abstractions.
Experimental results show that the method is applicable to
finite-state machine models of industrial scale and brings
considerable improvements in performance over other methods
HYPE with stochastic events
The process algebra HYPE was recently proposed as a fine-grained modelling
approach for capturing the behaviour of hybrid systems. In the original
proposal, each flow or influence affecting a variable is modelled separately
and the overall behaviour of the system then emerges as the composition of
these flows. The discrete behaviour of the system is captured by instantaneous
actions which might be urgent, taking effect as soon as some activation
condition is satisfied, or non-urgent meaning that they can tolerate some
(unknown) delay before happening. In this paper we refine the notion of
non-urgent actions, to make such actions governed by a probability
distribution. As a consequence of this we now give HYPE a semantics in terms of
Transition-Driven Stochastic Hybrid Automata, which are a subset of a general
class of stochastic processes termed Piecewise Deterministic Markov Processes.Comment: In Proceedings QAPL 2011, arXiv:1107.074
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