Neural Network Learning using Particle Swarm Optimizers
نویسندگان
چکیده
This paper presents a method to employ particle swarm optimization in a split architecture injected with a plain ‘attractor’ configuration. This is achieved by splitting the input vector into two even sub-vectors, each of which is optimized in its own swarm. Then, a plain ‘attractor’ is injected into each swarm. The application of this technique to neural network training is investigated. Key-Words: Particle Swarm, Neural Networks, Split Swarm
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