Dr. Kit Yan Chan

Curtin University, Australia



2006  Ph.D., London South Bank University, UK

Publications (selected)

  1. S.H. Ling, H.H.C. Iu, K.Y. Chan, H.K. Lam, C.W. Yeung, and F.H.F. Leung, Hybrid particle swarm optimization with wavelet mutation and its industrial applications, IEEE Transactions Systems, Man and Cybernetic - B, vol. 38, no. 3, pp. 743-763, 2008. (the applications are about power system stability)
  2. K.Y. Chan, K.F.C. Yiu, T.S. Dillon and S.H. Ling, Enhancement of speech recognitions for control automation using an intelligent particle swarm optimization, IEEE Transactions on Industrial Informatics, (accepted with minor revision).
  3. K.Y. Chan, K.W. Chan, G.T.Y. Pong, and M.E. Aydin, A statistics-based genetic algorithm for quality improvements of power supplies, European Journal of Industrial Engineering, vol. 3, no. 4, pp. 468-492, 2009.
  4. K.Y. Chan, S.H. Ling, K.W. Chan, G.T.Y. Pong, and H.H.C. Iu, Solving transient-stability constrained optimal power flow problems with wavelet mutation based hybrid particle swarm optimization, International Journal of Information and Systems Sciences, vol. 4, no. 4, pp. 585-601, 2008. (invited paper)
  5. K.Y. Chan, G. T. Y. Pong and K. W. Chan, Investigation of Hybrid Particle Swarm Optimization Methods for Solving Transient-Stability Constrained Optimal Power Flow Problems, Engineering Letters, Vol. 16, No. 1, pp. 61-67, 2008. (invited paper)
  6. K.Y. Chan, T.C. Fogarty, M. Emin Aydin, S.H. Ling, H.H.C. Iu, Genetic algorithms with dynamic mutation rates and their industrial applications, International Journal of Computational Intelligence and Applications, vol. 7, no. 2, pp. 103-128, 2008. (the applications are about power system stability)
  7. K.F.C. Yiu, K.Y. Chan, S.Y. Low, and S. Nordholm, A multi-filter system for speech enhancement under low signal-to-noise ratios, Journal of Industrial and Management Optimization, vol. 5, no. 3, pp. 671-682, 2009.
  8. K.Y Chan, T.S. Dillon and C.K. Kwong, Modeling a liquid epoxy molding process using a particle swarm optimization based fuzzy regression, IEEE Transactions on Industrial Informatics, 7(1), 148-158, 2011.
  9. C.K. Kwong, Y. Chen, K.Y. Chan and H. Wong, Hybrid fuzzy least-squares regression approach to modeling manufacturing processes, IEEE Transactions on Fuzzy Systems, 16(3) 644-651, 2008.
  10. K.Y Chan, C.K. Kwong, T.S. Dillon and Y.C. Tsim, Reducing overfitting in manufacturing process modeling using a backward elimination based genetic programming, Applied Soft Computing, Volume 11, Number 2, Pages 1648-1656, March 2011.
  11. K.Y Chan, T.S. Dillon and C.K. Kwong, Handling Uncertainties in Modelling Manufacturing Processes with Hybrid Swarm Intelligence, International Journal of Production Research 2011. (DOI: 10.1080/00207543.2011.560206)
  12. K.Y Chan, C.K. Kwong and T.C Fogarty, Modeling manufacturing processes using a genetic programming based fuzzy regression with the detection of outliers, Information Sciences, 180(4), 506-518, 2010.
  13. C.K. Kwong, K.Y. Chan and Y.C. Tsim, A genetic algorithm based knowledge discovery system for the design of fluid dispensing processes for electronic packaging, Expert Systems with Applications, Vol. 36, pp. 3829-3838, 2009.
  14. S.H. Ling, H.H.C. Iu, F.H.F. Leung and K.Y. Chan, Improved hybrid particle swarm optimized wavelet neural network for modelling the development of fluid dispensing for electronic packaging, IEEE Transactions on Industrial Electronics, 55(9), 3447-3460, September 2008.
  15. K.Y Chan, C.K. Kwong and Y.C Tsim, A fuzzy nonlinear regression based on genetic programming to modeling manufacturing processes, International Journal of Production Research, Vol. 48, No. 7, pp. 1967-1982, 2009.

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