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Due to the disadvantages of the ant algorithm used in the combining optimization in continuous space and the demerit of BP algorithm being vulnerable in the local optimum, the dynamics model of chaos ant colony has been introduced into the optimization of weights in neural network model. Therefore, the chaos ant colony neural network can have both extensive mapping ability of neural network and rapid...
The novel Imperialist Competitive Algorithm (ICA) that was recently introduced has a good performance in some optimization problems. The ICA inspired by sociopolitical process of imperialistic competition of human being in the real world. In this paper, a new Adaptive Imperialist Competitive Algorithm (AICA) is proposed. In the proposed algorithm, for an effective search, the Absorption Policy changed...
The traditional training method of synergetic neural network is to calculate prototype vector first, then adjoint vector is figured out from prototype vector according to certain rules, the whole course is slowly. The studying of potential energy function dynamics process can train prototype vector and adjoint vector meanwhile. The optimization approach is introduced to synergetic dynamics evolution...
An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of the trail information updating. The algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. The results of function optimization show that the algorithm has good searching ability and high convergence speed. The algorithm is employed to design a neuro-fuzzy controller...
A hybrid algorithm based on Extremal Optimization (EO) with adaptive levy mutation and Differential Evolution (HEODE) was proposed in this paper. It applied the idea of combination mechanism of global and local search. In the process of the global search, DE is an evolutionary algorithm based on the difference in group that can quickly approach a approximate optimal solution. During the local search,...
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