This work deals with an investigation on optimization of the feedback control of chaos based on using of the evolutionary algorithms. The main aim of this work is to show that evolutionary algorithms are capable of optimization of chaos control. As a model of deterministic chaotic system the Henon map was used. The optimizations were realized in several ways, each one for another set of paramet...

The firefly algorithm is a member of the swarm intelligence family of algorithms, which have recently showed impressive performances in solving optimization problems. The fire-fly algorithm, in particular, is applied for solving continuous and discrete optimization problems. In order to tackle different optimization problems efficiently and fast, many variants of the firefly algorithm have rece...

The quantum particle swarm optimization (QPSO) algorithm exists some defects, such as premature convergence, poor search ability and easy falling into local optimal solutions. The adaptive adjustment strategy of inertia weight, chaotic search method and neighborhood mutation strategy are introduced into the QPSO algorithm in order to propose an improved quantum particle swarm optimization (AMCQ...

Extended-range electric vehicle is considered to be the ideal transition type for electric vehicle. The optimal operation curve control strategy was proposed for a 12 meter-long range extended electric bus. With exponential function inertia weight adjustment and local chaos substitution, an improved chaotic particle swarm optimization algorithm was applied to optimize the key parameters of ener...

To solve chaotic time series prediction problem, a novel Prediction approach for chaotic time series based on Immune Optimization Theory (PIOT) is proposed. In PIOT, the concepts and formal definitions of antigen, antibody and affinity being used for time series prediction are given, and the mathematical models of immune optimization operators being used for establishing time series prediction ...

This paper proposes the application of chaos in large search space problems, and suggests that this represents the next evolutionary step in the development of adaptive and intelligent systems towards cognitive machines and systems. Three different versions of chaotic simulated annealing (XSA) were applied to combinatorial optimization problems in multiprocessor task allocation. Chaotic walks i...

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the chaotic systems theory, this paper proposed a novel chaotic PSO combined with an implicit filtering (IF) local search method to solve economic dispatch problems. Since chaotic mapping enjo...

We describe an algorithm for optimizing time-averaged objective functions that depend on a chaotic state variable. Such problems are ubiquitous in engineering design. They are challenging, because of the sensitive dependence of the state to perturbations in the design. One consequence of this sensitive dependence is that increasing the averaging period, which improves the accuracy of the object...

In this paper, a new method is presented for encryption of colored images. This method is based on using stack data structure and chaos which make the image encryption algorithm more efficient and robust. In the proposed algorithm, a series of data whose range is between 0 and 3 is generated using chaotic logistic system. Then, the original image is divided into four subimages, and these four i...