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Computational Intelligence-Based Parametrization on Force-Field Modeling for Silicon Cluster Using ASBO

  • S. N. Gondakar
  • S. T. Vasan
  • Manoj Kumar Singh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 380)

Abstract

A new parametrization of the small-size silicon cluster is proposed in this paper to improve the quality of predicted energy value by potential energy function in force-field modeling. ASBO-based concept has applied to evolve the parameters under different circumstances and cluster structure. The performance of new parameters is compared with the other well-established parameters in stillinger–weber energy function and its variants. Under known and unknown environment, effects of higher dimension in energy predicting capability are also analyzed. A significant improvement is observed in predicting the small cluster energy value with a proposed solution compared to values obtained with existing parameters. PSO with dynamic weight (DWPSO) is also applied to analyze the comparative capability of ASBO in solution exploration and convergence characteristics, and there is a remarkable improvement observed with ASBO-based solution.

Keywords

Nanotechnology Molecular force field Potential energy function Interatomic interaction Computational intelligence ASBO PSO 

Notes

Acknowledgments

This research has completed in Manuro Tech Research Pvt. Ltd., Bangalore, India. The Authors express their thanks to Mrs. Reeta Kumari (Director) for her valuable suggestion to accomplish this research.

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Copyright information

© Springer India 2016

Authors and Affiliations

  • S. N. Gondakar
    • 1
  • S. T. Vasan
    • 2
  • Manoj Kumar Singh
    • 3
  1. 1.Department of PhysicsVTUBelgaumIndia
  2. 2.Department of Engineering PhysicsRural Engineering CollegeHulkotiIndia
  3. 3.Manuro Tech Research Pvt. LtdBangaloreIndia

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