Design of evolutionary cubic spline intelligent solver for nonlinear Painlevé-I transcendent. (English) Zbl 1492.65038
Summary: In this research paper, an innovative bio-inspired algorithm based on evolutionary cubic splines method (CSM) has been utilized to estimate the numerical results of nonlinear ordinary differential equation Painlevé-I. The computational mechanism is used to support the proposed technique CSM and optimize the obtained results with global search technique genetic algorithms (GAs) hybridized with sequential quadratic programming (SQP) for quick refinement. Painlevé-I is solved by the proposed technique CSM-GASQP. In this process, variation of splines is implemented for various scenarios. The CSM-GASQP produces an interpolated function that is continuous upto its second derivative. Also, splines proved to be stable than a single polynomial fitted to all points, and reduce wiggles between the tabulated points. This method provides a reliable and excellent procedure for adaptation of unknown coefficients of splines by searching globally exploiting the performance of GA-SQP algorithms. The convergence, exactness and accuracy of the proposed scheme are examined through the statistical analysis for the several independent runs.
MSC:
| 65D07 | Numerical computation using splines |
| 34A34 | Nonlinear ordinary differential equations and systems |
| 41A15 | Spline approximation |
Keywords:
Painlevé I; cubic splines method; computational hybrid mechanism; genetic algorithm; sequential quadratic programming; numerical computingReferences:
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