Research Article
A New Stochastic Technique for Painlevé Equation-I Using Neural Network Optimized with Swarm Intelligence
Table 1
Parameter settings for ASA and PSO algorithms.
| |
PSO |
ASA | | Parameters | Setting | Parameters | Setting |
| | Swarm Size | 160 | Start Point | Best Particle of PSO | | Particle size | 30 | No. of variable | 30 | | Flights | 2000 | Iteration | 1000 | | Linear decreasing (2.5 to 0.5) | Maximum function Evaluations (MaxFunEvals) | 50000 | | Linear increasing (0.5 to 2.5) | Function tolerance (TolFun) | 10-18 | | Linearly decreasing (0.9 to 0.4) | Nonlinear Constraints tolerance (TolCon) | 10-18 | | 02 | Derivative approximate | Finite forward difference | | Population Span | (−50, 50) | X-Tolerance (TolX) | 10-12 | | Velocity Span | (−2, 2) | Bounds | (−50, 50) |
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