Control and synchronization of chaotic systems are studied.They are transformed into numerical optimization problems.A novel hybridization of differential evolution(DE) and bacterial foraging algorithm(BFOA),called CDEM algorithm,is proposed.The algorithm incorporates an adaptive chemotactic step from the BFOA into DE,which improves convergence of the classical DE.It introduces mutation operation of genetic algorithm for enhancing population diversity.Finally,CDEM algorithm is used to chaotic system control and synchronization.Numerical simulations based on Hénon Map demonstrate effectiveness and stability of the algorithm.Effects of parameters are investigated as well.

A new algorithm-particle swarm optimization (PSO), based on swarm intelligence, is applied to data processing of film parameters by ellipsometry. For a monolayer absorption film, reflective index, extinction coefficient and film thickness are obtained simultaneously by PSO. Even if the range of parameters is unknown, optimal solution can be obtained rapidly with search in a wide range. Compared with ellipsometry processing and genetic algorithm, the method exhibits high computational precision and high convergence speed.