Fuzzy Cellular Automata for Modeling Pattern Classifier
IEICE - Transactions on Information and Systems
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
RBFFCA: A Hybrid Pattern Classifier Using Radial Basis Function and Fuzzy Cellular Automata
Fundamenta Informaticae - Special issue on DLT'04
ENC '08 Proceedings of the 2008 Mexican International Conference on Computer Science
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There exist several ways to model population growth at present time, which are mainly based on mathematics. However we present a new model based on fuzzy cellular theory. An interval type-2 fuzzy logic system (IT2-FLS) is designed to evaluate the population growth parameters based on the environment resources stochasticity, in time and space. Interval type-2 fuzzy sets are used to measure the uncertainties of the environment resources. The main goal of this work is to demonstrate how the IT2-FLS integrated into a population growth model can make a suitable evaluation of the parameters required to make that the population size reach a stable equilibrium level on which it fluctuates into a time interval and after that, population size goes down as consequence of insufficient resources. This behaviour is the fundamental basis of the majority of the mathematical models made through the years in Ecology to study the population dynamics.