A steganographic method based upon JPEG and particle swarm optimization algorithm
Information Sciences: an International Journal
Comparison between Adomian's method and He's homotopy perturbation method
Computers & Mathematics with Applications
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Information Sciences: an International Journal
A numerical methodology for the Painlevé equations
Journal of Computational Physics
A new stochastic approach for solution of Riccati differential equation of fractional order
Annals of Mathematics and Artificial Intelligence
Numerical treatment of nonlinear Emden---Fowler equation using stochastic technique
Annals of Mathematics and Artificial Intelligence
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A methodology for solution of Painlevé equation-I is presented using computational intelligence technique based on neural networks and particle swarm optimization hybridized with active set algorithm. The mathematical model of the equation is developed with the help of linear combination of feed-forward artificial neural networks that define the unsupervised error of the model. This error is minimized subject to the availability of appropriate weights of the networks. The learning of the weights is carried out using particle swarm optimization algorithm used as a tool for viable global search method, hybridized with active set algorithm for rapid local convergence. The accuracy, convergence rate, and computational complexity of the scheme are analyzed based on large number of independents runs and their comprehensive statistical analysis. The comparative studies of the results obtained are made with MATHEMATICA solutions, as well as, with variational iteration method and homotopy perturbation method.