We present a method for modeling user navigation on a web site using grammatical inference of stochastic regular grammars. With this method we achieve better models than the previously used first order Markov chains, in terms of predictive accuracy and utility of recommendations. In order to obtain comparable results, we apply the same grammatical inference algorithms on Markov chains, modeled ...

We propose in this thesis several contributions related to the quantitative verification of systems. This discipline aims to evaluate functional and performance properties of a system. Such a verification requires two ingredients: a formal model to represent the system and a temporal logic to express the desired property. Then the evaluation is done with a statistical or numerical method. The s...

This paper considers the issue of developing approximate abstractions of stochastic hybrid systems. The stochastic continuous behaviour breaks many essential properties of hybrid automata. Our approach departs from the progress in stochastic reachability analysis and Markov chain approximations. For this purpose we have to introduce a new approximation scheme and look for a suitable metric. We ...

Using hybrid automata, one is able to model many types of systems and express their properties in various formal languages. Being extremely general and rich, however, the class of hybrid automata exhibits the inherent problems of automata theory: even the simplest of properties for general hybrid automata are undecidable. Therefore, one must restrict attention only to subclasses of this very ge...

A hybrid automaton is a model of a system with interacting continuous and discrete dynamics. It has been successfully employed in emerging applications on the border between computer science and control theory. In this paper, hybrid automata are formally introduced. Some results on existence and uniqueness of executions for hybrid automata are obtained. Continuous dependence on initial states a...

Cycle-linear hybrid automata (CLHAs), a new model of excitable cells that efficiently and accurately captures action-potential morphology and other typical excitable-cell characteristics such as refractoriness and restitution, is introduced. Hybrid automata combine discrete transition graphs with continuous dynamics and emerge in a natural way during the (piecewise) approximation process of any...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

FAULT DIAGNOSIS OF HYBRID SYSTEMS WITH APPLICATIONS TO GAS TURBINE ENGINES Rasul Mohammadi, Ph.D. Concordia University, 2009 Stringent reliability and maintainability requirements for modern complex systems demand the development of systematic methods for fault detection and isolation. Many of such complex systems can be modeled as hybrid automata. In this thesis, a novel framework for fault di...

Markov chains are a well-known stochastic process that provide a balance between being able to adequately model the system’s behavior and being able to afford the cost of the model solution. Systems can be modeled directly as Markov chains, or with a higher-level formalism for which Markov chains represent the underlying semantics. Markov chains are widely used to study the performance of compu...