High security has always been the ultimate goal of image encryption, and closer ciphertext is to true random number, higher security. Aiming at popular chaotic encryption methods, particle swarm optimization (PSO) studied select parameters initial values systems so that sequence entropy. Different from other PSO-based proposed method takes system as particles instead encrypted images, which mak...

The control approach for chaotic systems is one of the hottest research topics in nonlinear area. This paper is concerned with the controller design problem for chaotic systems. The particle swarm optimization (PSO) algorithm is firstly proposed to search for the weights of the Chebyshev neural networks (CNNs), and then an adaptive controller for the chaotic systems is designed based on the PSO...

To overcome the problem of premature convergence on Particle Swarm Optimization (PSO), this paper proposes both the improved particle swarm optimization methods (IPSO) based on self-adaptive regulation strategy and the Chaos Theory. Given the effective balance of particles’ searching and development ability, the self-adaptive regulation strategy is employed to optimize the inertia weight. To im...

This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust t...

this paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. the model makes use of the newly introduced particle swarm optimization algorithm. a two step optimization model is developed and solved with the particle swarm optimization method. the model first carries out an exhaustive enumeration search for all feasible sets of p...

Today the Genetic Algorithm (GA) is used to solve a large variety of complex nonlinear optimization problems. However, permute convergence which is one of the most important disadvantages in GA is known to increase the number of iterations for reaching a global optimum. This paper, presents a new GA based on chaotic systems to overcome this shortcoming,. We employ logistic map and tent map as t...