Dr. Steve Sai Ho Ling

University of Technology Sydney, Australia

Email: steve.ling@uts.edu.au

Qualifications

2006  Ph.D., The Hong Kong Polytechnic University, Hong Kong, China

2002  M.Phil., The Hong Kong Polytechnic University, Hong Kong, China

1999  B.Eng., The Hong Kong Polytechnic University, Hong Kong, China

Publications (selected)

1. S.H. Ling, Genetic Algorithm and Variable Neural Networks: Theory and Application, Lambert Academic Publishing, German, 2010, ISBN: 978-3-8433-6729-5.
2. H.K. Lam, S.H. Ling, and H.T. Nguyen, Eds., Computational Intelligence and Its Applications: Evolutionary Computation, Fuzzy Logic, Neural Network and Support Vector Machine Techniques, World Scientific, UK, Aug 2012, ISBN: 978-1-8481-6691-2.
3. P.P. San,S.H. Ling,and H.T. Nguyen, “Industrial Application of Evolvable Block-Based Neural Network to Hypoglycemia Monitoring System,” IEEE Trans. Industrial Electronics, 2012 (in-press).
4. S.H. Ling,P.P. San, H.T. Nguyen, and F.H.F. Leung, “Non-invasive nocturnal hypoglycemia detection for insulin-dependent diabetes mellitus using genetic fuzzy logic method,” Int. J. Computational Intelligence and Applicat, 2012 (in-press).
5. P.P. San,S.H. Ling,and H.T. Nguyen, “Application of optimized variable translation wavelet neural network in hypoglycemia detection system,” Neural Computing and Applications, 2012 (in-press).
6. J.C.Y. Lai, F.H.F. Leung, S.H. Ling and H.T. Nguyen, “Hypoglycaemia detection using fuzzy inference system with multi-objective double wavelet mutation differential evolution,” Applied Soft Computing,2012(in-press)
7. K.Y. Chan, C.K.F. Yiu, T.S. Dillon, S. Nordholmand, and S.H. Ling,“Enhancement of speech recognitions for control automation using an intelligent particle swarm optimization,” IEEE Trans on Ind. Informatics, vol. 8, no. 4, pp. 869–879, Nov, 2012.
8. S.H. Ling and H.T. Nguyen, “Natural occurrence of nocturnal hypoglycemia detection using hybrid particle swarm optimized fuzzy reasoning model,” Artificial Intell.inMedicine,vol. 55, no. 3, pp. 177–184, July, 2012.
9. J.C.Y. Lai, F.H.F. Leung, S.H. Ling and E. C. Shi, “An Improved differential evolution and its industrial application,” Journal of Intelligence Learning Systems and Application, vol. 4, no. 2, pp. 81–97, May, 2012.
10. N. Nuryani, S.H. Ling,and H.T. Nguyen, “Electrocardiographic signals and swarm based support vector machine for hypoglycemia detection,” Annals of Biomedical Engineering , vol. 40, no. 4, pp. 934–945, Apr, 2012.
11. S.H. Ling, F. Jiang, K.Y. Chan, and H.T. Nguyen,“Hybrid fuzzy logic-based particle swarm optimization for flow shop scheduling problem,” Int. J. Computational Intelligence and Applicat.,vol. 10, no. 3, pp. 335–356, Sep, 2011.
12. K.Y. Chan, S.H. Ling, T.S. Dillion, and H.T. Nguyen, “Diagnosis of hypoglycemic episodes using a neural network based rule discovery system,” Expect system and Applications, vol. 38, no. 8, pp. 9799–9808, Aug, 2011.
13. D. Dehestani, F.Eftekhari, Y. Guo, S. H. Ling, S. Su, H.T. Nguyen, “Online support vector machine application for model based fault detection and isolation of HVAC system,” International Journal of Machine Learning and Computing, vol. 1, no. 1, pp. 66–72. Apr, 2011.
14. S.H. Ling and H.T. Nguyen, “Genetic algorithm based multiple regression with fuzzy inference system for detection of nocturnal hypoglycemic episodes,” IEEE Trans. on Information Technology in Biomedicine, vol. 15, no. 2, pp. 308–315, Feb, 2011.
15. S.H. Ling and H.K. Lam, “Playing Tic-Tac-Toe using genetic neural network with double transfer functions,” Journal of Intelligence Learning Systems and Application, vol. 3, no. 1, pp. 37–44, Feb, 2011.
16. Y. Liu, B. Liu, andS.H. Ling, “The almost periodic solution of lotka-volterrarecurrent neural networks with delays,”Neurocomputing, vol. 74, no. 6, Feb, pp. 1062–1068, 2011.
17. S.H. Ling, “A new neural network structure: node-to-node-link neural network,” Journal of Intelligence Learning Systems and Application,vol. 2, no. 1, pp. 1–11, Feb, 2010.
18. K.Y. Chan, K.W. Chan, Glory T.Y. Pong,M. Emin Aydin,T.C. Fogarty and S.H. Ling, “A statistics-based genetic algorithm for quality improvements of power supplies,” European Journal of Industrial Engineering, vol. 3, no. 4, pp. 468–492, 2009.
19. S.H. Ling, F.H.F Leung, H.K. Lam, and H.C.C. Iu, "Variable-structure neural network with real-coded genetic algorithm and its application on electric short-term load forecasting," Int. J Information and System Sciences.,vol. 5, no. 1, pp. 23–40, Jan. 2009.
20. F.H.F. Leung,S.H. Ling, and H.K. Lam," Animproved genetic-algorithm-based neural-tuned neural network," International Journal of Computational Intelligence and Applications,vol. 7, no. 4, pp. 469–492, Dec. 2008.
21. K.Y. Chan,M. Emin Aydin, S.H. Ling, T.C. Fogarty, and 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, Jun. 2008.
22. S.H. Ling,H.H.C Iu, F.H.F. Leung,and K.Y. Chan, “Improved hybrid PSO-based wavelet neural network for modelling the development of fluid dispensing for electronic packaging,”IEEE Trans. Industrial Electronic,vol. 55, no. 9, pp. 3447–3460, Sep. 2008.
23. 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,” Int. J Information and System Sciences, vol. 4, no. 4, pp. 585–601, Sep. 2008.
24. J.H.C Hga, H.H.C. Iu, S.H. Ling, and H.K. Lam, “Comparative study of stability in different TCP/RED models,” Chaos, Solitons& Fractals,vol. 37, no. 4, pp. 977–987, Aug. 2008.
25. S.H. Ling, H.C.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 Trans. Sys., Man, and Cybernetics, Part B, vol. 38, no. 3, pp. 743–763, Jun. 2008.
26. H.K. Lam, B.W.K. Ling, H.H.C. Iu, and S.H. Ling, “Synchronization of chaotic systems using time-delayed fuzzy state-feedback controller,”IEEE Trans Circuit and Sys. I,vol. 55, no. 3, pp. 893-903, Apr. 2008.
27. S.H. Ling, H.K. Lam, and F.H.F. Leung, “Input-dependent neural network trained by improved genetic algorithm and its application,”Soft Computing,vol. 11, no. 11, pp. 1033–1052, Sep. 2007.
28. K.F. Leung, F.H.F. Leung, H.K. Lam and S.H. Ling, "Application of a modified neural fuzzy network and improved genetic algorithm to speech recognition," Neural Computing and Application,vol. 16, no. 4–5, pp. 419–431, May. 2007.
29. S.H. Ling and F.H.F Leung, "An improved genetic algorithm with average-bound crossover and wavelet mutation operations," Soft Computing,vol. 11, no. 1, pp. 7–31, Jan. 2007.
30. S.H. Ling, F.H.F Leung and H.K. Lam, "An improved genetic algorithm based fuzzy-tuned neural network," Int. J. Neural systems,vol. 15, no. 6, pp. 457–474, Dec. 2005.
31. S.H. Ling, F.H.F. Leung, L.K. Wong, and H.K. Lam," Computational Intelligence techniques for Home Electric Load Forecasting and Balancing," International Journal of Computational Intelligence and Applications,vol. 5, no. 3, pp. 371–391, Sep. 2005.
32. H.K. Lam, S.H. Ling, F.H.F. Leung, and P.K.S. Tam, “Function estimation using a neural-fuzzy network and an improved genetic algorithm,” International Journal of Approximate Reasoning, vol. 30, no. 3, pp. 243–260, Jul. 2004
33. F.H.F Leung, H.K. Lam, S.H. Ling, and P.K.S. Tam, “Optimal and stable fuzzy controllers for nonlinear systems using an improved genetic algorithm,” IEEE Trans. Industrial Electronics, vol. 51, no. 1, pp.172–182, Feb. 2004.
34. K.F. Leung, F.H.F. Leung, H.K. Lam, and S.H. Ling, “On interpretation of graffiti digits and commands for eBooks: neural-fuzzy network and genetic algorithm Approach,” IEEE Trans. Industrial Electronics, vol. 51, no. 2, pp.464–471, Apr. 2004.
35. S.H. Ling, F.H.F Leung, H.K. Lam, and P.K.S. Tam, “Short-term electric load forecasting based on a neural fuzzy network,” IEEE Trans. Industrial Electronics, vol. 50, no. 6, pp.1305–1316, Dec. 2003.
36. S.H. Ling, F.H.F. Leung, H.K. Lam, Y.S. Lee, and P.K.S. Tam, “A novel GA-based neural network for short-term load forecasting,” IEEE Trans. Industrial Electronics, vol. 50, no. 4, pp.793–799, Aug. 2003.
37. F.H.F. Leung, H.K. Lam, S.H. Ling, and P.K.S. Tam, “Tuning of the structure and parameters of neural network using an improved genetic algorithm,” IEEE Trans. Neural Networks, vol.14, no. 1, pp.79–88, Jan. 2003.

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