New generalized chaos-geometric and neural networks approach to nonlinear dynamics of the complex systems

Abstract

We present a new generalized approach to modeling nonlinear processes of chaotic systems based on the known concept of compact geometric attractors, chaos theory methods in effective realization plus implemented neural networks simulation algorithm. Using information on the phase space evolution of the nonlinear process in time and the neural networks simulation techniques can be considered as one of the fundamentally new approaches in the construction of global nonlinear prediction models for evolutionary dynamics of the complex chaotic systems and accurate description of the structure of the corresponding strange attractors