In this study an efficient meta-heuristic is proposed for layout optimization of truss structures by combining cellular automata (CA) and firefly algorithm (FA). In the proposed meta-heuristic, called here as cellular automata firefly algorithm (CAFA), a new equation is presented for position updating of fireflies based on the concept of CA. Two benchmark examples of truss structures are presen...

Markov automata are a compositional modelling formalism with continuous stochastic time, discrete probabilities, and nondeterministic choices. In this article, we present extensions to M ODEST , an expressive high-level language roots in process algebra, that allow large models be specified succinct, modular way. We illustrate the advantages of over alternative languages. Model checking require...

Monitoring urban area expansion through multispectral remotely sensed data and other geomatics techniques is fundamental for sustainable planning. Forecasting of future land use cover (LULC) change the years 2034 2050 was performed using Cellular Automata Markov model current fast-growing Epworth district Harare Metropolitan Province, Zimbabwe. The stochastic CA–Markov modelling procedure valid...

We consider a generalized model of a probabilistic cellular automata described by a Markov chain on an infinite dimensional space and derive certain large deviations bounds for corresponding occupational measures.

Urbanization is one of the biggest challenges for developing countries, and predicting urban growth can help planners policymakers understand how spatial patterns interact. A study was conducted to investigate spatiotemporal dynamics land use/land cover changes in Salem its surrounding communities from 2001 2020 simulate expansion 2030 using cellular automata (CA)–Markov geospatial techniques. ...

In this paper we consider cellular automata (G,Φ) with algebraic local rules and such that G is a topological Markov chain which has a structure compatible to this local rule. We characterize such cellular automata and study the convergence of the Cesàro mean distribution of the iterates of any probability measure with complete connections and summable decay. Subj-class: DS, PR, CO. MSC-class: ...

We propose algorithms that use Markov chain techniques to generate acyclic automata uniformly at random. We first consider deterministic, accessible and acyclic automata, then focus on the class of minimal acyclic automata. In each case we explain how to define random local transformations that describe an ergodic and symmetric Markov chain: the distribution of the automaton obtained after T ra...