Abstract
We presented a method for van der Pol oscillators using artificial neural network optimized by evolutionary computational approach. A trail solution of the oscillator is written as a feed-forward neural network containing adjustable adaptive parameters. The optimization of the networks is performed by genetic algorithms in an unsupervised way. The proposed scheme is tested successfully by applying on both the stiff and non-stiff problems. A Monte Carlo simulation is performed for the reliability and effectiveness of the scheme. It is shown that the obtained results are in good agreement with Runge Kutta numerical method. Key words: Van der pol oscillator, genetic algorithms, neural network modeling.
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