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Bio-inspired computational heuristics to study Lane–Emden systems arising in astrophysics model
This study reports novel hybrid computational methods for the solutions of nonlinear singular Lane–Emden type differential equation arising in astrophysics models by exploiting the strength of unsupervised neural network models and stochastic optimization techniques. In the scheme the neural network...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5078133/ https://www.ncbi.nlm.nih.gov/pubmed/27822440 http://dx.doi.org/10.1186/s40064-016-3517-2 |