A particle swarm optimization approach to nonlinear rational filter modeling

Expert Systems with Applications

Volumn 34, Issue 2, 2008, Pages 1194-1199

  Lin, Yih Lon ^a   Chang, Wei Der ^b   Hsieh, Jer Guang ^c  

^a I SHOU UNIVERSITY   (Taiwan)

^b SHU TE UNIVERSITY   (Taiwan)

^c NATIONAL SUN YAT SEN UNIVERSITY   (Taiwan)

Author keywords

Nonlinear rational filter; Parameter estimation; Particle swarm optimization (PSO)

Indexed keywords

COMPUTER PROGRAM LISTINGS; MATHEMATICAL MODELS; NONLINEAR SYSTEMS; PARAMETER ESTIMATION; VECTORS;

BINARY STRINGS; NONLINEAR RATIONAL FILTER; PARTICLE SWARM OPTIMIZATION (PSO); REAL NUMBERS;

GENETIC ALGORITHMS;

EID: 36148988439     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2006.12.004     Document Type: Article

References (14)

1. Abido M.A. Optimal design of power-system stabilizers using particle swarm optimization. IEEE Transactions on Energy Conversion 17 (2002) 406-413
2. El-Zonkoly A.M. Optimal tuning of power systems stabilizers and AVR gains using particle swarm optimization. Expert Systems with Applications 31 (2006) 551-557
3. Gaing Z.L. A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Transactions on Energy Conversion 19 (2004) 384-391
4. Ganguli R. Noise and outlier removal from jet engine health monitoring signals using weighted FIR median hybrid filters. Mechanical Systems and Signal Processing 16 6 (2002) 867-978
5. Kenny, J., & Eberhart, R. (1995). Particle swarm optimization. In: Proceedings of IEEE international conference neural networks (pp. 1942-1948), (Vol. IV). Perth, Australia.
6. Lin C.T., and Juang C.F. An adaptive neural fuzzy filter and its applications. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 27 4 (1997) 635-656
7. Liu B., Wang L., Jin Y.H., Tang F., and Huang D.X. Improved particle swarm optimization combined with chaos. Chaos, Solitons and Fractals 25 (2005) 1261-1271
8. Nounou M.N., and Bakshi B.R. On-line multiscale filtering of random and gross errors without process models. AIChE Journal 45 5 (1999) 1041-1058
9. Shi, Y., & Eberhart, R.C. (1998). A modified particle swarm optimization. In proceedings of the IEEE international conference evolution computer (pp. 69-73). Anchorage.
10. Shi, Y., & Eberhart, R.C. (1999). Empirical study of particle swarm optimization. In proceedings of the IEEE international conference evolution computer (pp. 1945-1950). Washington, DC.
11. Van de Vegte J. Fundamentals of digital signal processing (2001), Prentice Hall, New Jersey
12. Yin P.Y. A discrete particle swarm algorithm for optimal polygonal approximation of digital curves. Journal of Visual Communication and Image Representation 15 (2004) 241-260
13. Yu, K.W., & Hu, S.C. (2006). An application of AC servo motor by using particle swarm optimization based sliding mode controller. In proccedings of the IEEE international conference on systems, man and cybernetics (pp. 4146-4150). Taipei, Taiwan.
14. Zhu Q.M. A back propagation algorithm to estimate the parameters of nonlinear dynamic rational models. Applied Mathematical Modeling 27 (2003) 169-187