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In this paper, a novel evolutionary algorithm for many-objective optimization is proposed. The algorithm adopts a new global ranking method to favor convergence and an improved crowding distance to maintain diversity, new elitist selection strategy Based on fitness evaluation is also designed to guide the search towards a representative approximation of the Pareto-optimal front. In order to validate...
In this paper, a type of chaotic recurrent fuzzy neural network (CRFNN) model is proposed. The CRFNN model add chaotic map in the membership function layer of a RFNN. A generalized dynamic back propagation algorithm (DBP) is developed to automatically construct the CRFNN. To guarantee the convergence by Lyapunov function, the online learning rate adjusting range is given. Simulation results of identifying...
A novel hybrid particle swarm optimization (HPSO) is proposed, which the gradient descent learning algorithm is combined with modified particle swarm optimization (MPSO). Firstly, the MPSO was determined by linearly decreasing inertia weight and constriction factor weight to speed up global search, also crossover and mutation operation was embedded to avoid the common defect of premature convergence...
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