Quick population increase and the desire for urbanization are main drivers accelerating urban expansion on agricultural lands in Egypt. This issue is obvious governorates with no desert backyards. study aims to (1) explore trend of Land Use Cover Change (LULCC) through period 1991–2018; (2) upgrade reliability predicting LULCC by integrating Cellular Automata (CA)-Markov chain fuzzy analytical ...

In this study we model the daily rainfall occurrence using Markov Chain Analogue Yearmodel (MCAYM) and the intensity or amount of daily rainfall using three different probability distributions; gamma, exponential and mixed exponential distributions. Combining the occurrence and intensity model we obtain Markov Chain Analogue Year gamma model (MCAYGM), Markov Chain Analogue Year exponentia...

a r t i c l e i n f o a b s t r a c t To study the effects of a delayed immune-response on the growth of an immunogenic neoplasm we introduce Stochastic Hybrid Automata with delayed transitions as a representation of hybrid biochemical systems with delays. These transitions abstractly model unknown dynamics for which a constant duration can be estimated, i.e. a delay. These au-tomata are inspir...

| This paper gives a brief overview on statistical classiication of time series using Hidden Markov Models. To overcome some limitations and assumptions made in the Hidden Markov Model framework two successful hybrid extensions using Neural Networks are presented. At rst, a short description of traditional stochastic-based Hidden Markov Model classiiers with diierent kinds of emission probabili...

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a du...

In this paper we present a new symbolic, computer algebra based approach to hybrid systems. Hybrid systems are systems containing both, continuous and discrete changing quantities. As is commonly done, we model hybrid systems using hybrid automata. Hybrid automata extend the classical notion of finite state machines by combining differential equations to model the dynamic behavior of systems wi...

In this paper, we present a new tool SReach, which solves probabilistic bounded reachability problems for two classes of models of stochastic hybrid systems. The first one is (nonlinear) hybrid automata with parametric uncertainty. The second one is probabilistic hybrid automata with additional randomness for both transition probabilities and variable resets. Standard approaches to reachability...

ion methods are used to simplify models and make their analysis more tractable. Several equivalence relations have been studied for subclasses of hybrid systems. For example, it can be shown that transition systems of timed automata admit finite state abstractions, called region graphs, that are time-abstract bisimilar, see [AD94] for details. Those equivalence results are used to prove decidab...

Abstract In this work, we study a class of hybrid models for the stock market to account for the coexistence of continuous dynamics and discrete events. Different from the original geometric Brownian motion models, both the rate of return and the volatility in the hybrid model depend on a continuous-time Markov chain. This model can deal with random volatility by incorporating market trend with...

A discrete event system (DES) is a dynamic system that evolves in accordance with the abrupt occurrence, at possibly unknown irregular intervals, of physical events. Because of the special nature of these systems, different tools are currently used for their analysis, design and modeling. The main focus of this paper is the presentation of a new modeling approach of Discrete Event Systems. The ...