Self-similar inverse semigroups are defined using automata theory. Adjacency semigroups of s-resolved Markov partitions of Smale spaces are introduced. It is proved that a Smale space can be reconstructed from the adjacency semigroup of its Markov partition, using the notion of the limit solenoid of a contracting self-similar semigroup. The notions of the limit solenoid and a contracting semigr...

This study presents an effort to track and model land use change in the Twin Cities Metropolitan Region. To that end, we make use of a unique, high-resolution, cell-level set of land use data for the Twin Cities. The data represent 75 meter by 75 meter land use cells, observed at several points in time during the period from 1958 to 2005. These data are used to validate three different types of...

Finding a ground state of given Hamiltonian an Ising model on graph $$G=(V,E)$$ is important but hard problem. The standard approach for this kind problem the application algorithms that rely single-spin-flip Markov chain Monte Carlo methods, such as simulated annealing based Glauber or Metropolis dynamics. In paper, we investigate particular stochastic cellular automata, in which all spins are...

In order to control the development of urban space, it is important explore scientific methods provide a reference for regional territorial space planning. On basis minimum cumulative resistance (MCR) model and cellular automaton (CA)-Markov model, we constructed new technical method delineating boundaries, exploring temporal spatial distribution characteristic land use in Wuhan from 2010 2020 ...

Cellular automata (CA) is an important modelling paradigm for complex systems. In the design of cellular automata, most difficult task to find transformation rules that describe temporal evolution or pattern a modelled system. A CA with weights(CAW) yields transition algorithm proposed in this paper, which have ample physical meanings and extend category CA. Firstly, weights are increased conne...

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...