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This paper presents an improved PSO algorithm (TPSO) with dynamic parameter selection, in which the inertia weight and acceleration coefficients are defined by trigonometric functions of the present iterative generation. Compared with some typical PSO models, TPSO shows its superiority in convergence, robustness and solution quality through experimental tests with 8 widely used benchmark functions.
In order to determine the weights coefficient of the attributes and the times in dynamic multi-attribute system, based on trigonometrically function, a sine method is presented in this paper. Based on alternative matrix, the developing property of each attribute on the system is fully considered. According to sine function value, a new method to the uncertain multi-attribute decision-making problem...
This paper presents a beam pattern synthesis method for low cost implementation of antenna arrays. Instead of designing array weights, our method synthesizes unequally-spaced array with uniform antenna weights. The effect of mutual coupling is considered when we search a set of optimum antenna positions. The determination of the antenna positions is a nonlinear optimization problem because the positions...
Chaotic neural network has been proved to be a powerful tool to solve combinational optimization problems. A novel transiently chaotic neuron was presented by transferring sigmoid activation function into non-monotonous activation function composed of trigonometric function and sigmoid. The reversed bifurcation and the maximum Lyapunov exponent of the chaotic neuron were given and the dynamic system...
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