UPDATING TECHNIQUE FOR PARTICLE SWARM OPTIMIZATION IN NONLINEAR DYNAMIC SYSTEMS

Syahrulanuar Ngah, Zhu Hui, Takaaki Baba

2009

Abstract

Dealing with searching and tracking an optimal solution in dynamic environment becomes more frequently nowadays. For dealing with this matter, Particle Swarm Optimization – Random Times Variable Inertia Weight and Acceleration Coefficient (PSO-RTVIWAC) concept, motivated by Particle Swarm Optimization-Time Variable Acceleration Coefficient (PSO-TVAC) and Particle Swarm Optimization-Random Inertia Weight (PSO-RANDIW) was introduced. PSO-RTVIWAC can accomplish an acceptable accuracy in detecting the target with the small number of particle and iteration. This paper will discuss about modifying the fitness value in the update mechanism for determining the local best and global best to improve the accuracy of detecting the target. By adding a constant value to the current stored fitness value, it will give the opportunity to the next fitness value to be the best fitness value. The result from this modifying technique then will be compared with PSO-RTVIWAC to evaluate the performance.

References

  1. H. Zhu, S. Ngah, Y. Xu, Y. Tanabe and T. Baba “A Random Time-varying Optimization for Local Positioning Systems” Int. journal of Computer Science and Network Security, Vol 8 N0 6, 2008.
  2. X. Cui, C.T. Hardin, R.K. Ragade, T.E. Potok and A.S. Elmaghraby “Tracking non-Optimal Solution by Particle Swarm Optimizer” IEEE, Proc. Of Sixth Int. Conf. on Software Engineering, Artificial Intelligent, Networking and Parallel/Distributed Computing, 2005.
  3. R. C. Eberhart and J. Kennedy, “A new optimizer using particle swarm theory”, Proc. of the Sixth International Symposium on Micro Machines and Human Science, pp. 39-43, 1995
  4. R. C. Eberhart and Y. Shi, “Particle swarm optimization: developments, applications and resources”, Proceedings of the 2001 Congress on Evolutionary Computation, vol. 1, pp. 81-86, 2001
  5. E. Ozcanand and C.K. Mohan, “Particle swarm optimization: Surfing the waves,” in Proc. IEEE Congr. Evolutionary Computation 1999, vol. 3, Washington, DC, pp. 1944-1949, 1999.
  6. Y. Shi and R. C. Eberhart, “A modified particle swarm optimizer,” in Proc. IEEE Int. Conf. Evolutionary Computation, pp. 69-73, 1998
  7. R. C. Eberhart and Y. Shi, “Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization,” Congress on Evolutionary Computing, vol. 1, pp. 84-88, 2000.
  8. R. C. Eberhart and Y. Shi, “Comparison between genetic algorithms and particle swarm optimization,” The 7th Annual Conference on Evolutionary Programming, pp. 611-615, 1998.
  9. M. Clerc, “The swarm and the queen: towards a deterministic and adaptive particle swarm optimization,” Proc. CEC 1999, Washington, DC, pp 1951-1957, 1999.
  10. Y. Liu, Z. Qina, Z. Shi, J. Lu “Center Particle Swarm Optimization” Neurocomputing 70 (2007) pp. 672 - 679. www.sciencedirect.com.
  11. R. C. Eberhart and Y. Shi, “Tracking and optimizing dynamic systems with particle swarms,” in Proc. IEEE Congr. Evolutionary Computation 2001, Seoul, Korea, pp. 94-97, 2001
  12. M. Clerc and J. Kennedy, “The particle swarm: Explosion, stability, and convergence in a multidimensional complex space,” IEEE Transactions on Evolutionary Computation, pp. 58-73, 2002
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Paper Citation


in Harvard Style

Ngah S., Hui Z. and Baba T. (2009). UPDATING TECHNIQUE FOR PARTICLE SWARM OPTIMIZATION IN NONLINEAR DYNAMIC SYSTEMS . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 462-468. DOI: 10.5220/0001656704620468


in Bibtex Style

@conference{icaart09,
author={Syahrulanuar Ngah and Zhu Hui and Takaaki Baba},
title={UPDATING TECHNIQUE FOR PARTICLE SWARM OPTIMIZATION IN NONLINEAR DYNAMIC SYSTEMS},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={462-468},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001656704620468},
isbn={978-989-8111-66-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - UPDATING TECHNIQUE FOR PARTICLE SWARM OPTIMIZATION IN NONLINEAR DYNAMIC SYSTEMS
SN - 978-989-8111-66-1
AU - Ngah S.
AU - Hui Z.
AU - Baba T.
PY - 2009
SP - 462
EP - 468
DO - 10.5220/0001656704620468


in Harvard Style

Ngah S., Hui Z. and Baba T. (2009). UPDATING TECHNIQUE FOR PARTICLE SWARM OPTIMIZATION IN NONLINEAR DYNAMIC SYSTEMS.In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 462-468. DOI: 10.5220/0001656704620468


in Bibtex Style

@conference{icaart09,
author={Syahrulanuar Ngah and Zhu Hui and Takaaki Baba},
title={UPDATING TECHNIQUE FOR PARTICLE SWARM OPTIMIZATION IN NONLINEAR DYNAMIC SYSTEMS},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={462-468},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001656704620468},
isbn={978-989-8111-66-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - UPDATING TECHNIQUE FOR PARTICLE SWARM OPTIMIZATION IN NONLINEAR DYNAMIC SYSTEMS
SN - 978-989-8111-66-1
AU - Ngah S.
AU - Hui Z.
AU - Baba T.
PY - 2009
SP - 462
EP - 468
DO - 10.5220/0001656704620468