Applying Inhomogeneous Probabilistic Cellular Au-tomata Rules on Epidemic Model
M. Wesam, Habiba Ahmed, Fahmi Elsayed · INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ARTIFICIAL INTELLIGENCE · 2013
This paper presents some of the results of our probabilis¬tic cellular automaton (PCA) based epidemic model. It is shown that PCA performs better than deterministic ones. We consider two possible ways of interaction that relies on a two-way split rules either horizontal or vertical interaction with 2 different probabilities causing more of the best possible choices for the behavior of the disease. Our results are a generalization of that Hawkins et al done.