Input-dependent neural network trained by real-coded genetic algorithm and its industrial applications

Soft Computing

Volumn 11, Issue 11, 2007, Pages 1033-1052

  Ling, Steve H ^a   Leung, F H F ^b   Lam, H K ^c  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

Hand written recognition; Neural network; Real coded genetic algorithm; Short term load forecasting

Indexed keywords

CHARACTER RECOGNITION; FORECASTING; GENETIC ALGORITHMS; INDUSTRIAL APPLICATIONS; LEARNING ALGORITHMS;

GRAFFITI RECOGNITION; HAND-WRITTEN RECOGNITION; INPUT-DEPENDENT NEURAL NETWORK (IDNN); SHORT-TERM LOAD FORECASTING;

NEURAL NETWORKS;

EID: 34249894779     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-007-0151-5     Document Type: Article

References (48)

1. Aggarwal R, Song YH (1998) Artificial neural networks in power systems. Power Eng J, pp 279-287
2. Buse R, Liu ZQ, Bezdek J (2002) Word recognition using fuzzy logic. IEEE Trans Fuzzy Syst 10(1):65-76
3. Charytoniuk W, Chen MS (2000) Very short-term load forecasting using artificial neural networks. IEEE Trans Power Syst 15(1):263-268
4. Daubechies I (1990) The wavelet transform, time-frequency localization and signal analysis. IEEE Trans Inf Theory 36(5):961-1005
5. Davis L (1991) Handbook of genetic algorithms. Van Nostrand Reinhold, New York
6. Drezga I, Rahman S (1999) Short-term load forecasting with local ANN predictors. IEEE Trans Power Syst 14(3):844-850
7. Fieldsend JE, Singh S (2005) Pareto evolutionary neural networks. IEEE Trans Neural Netw 16(2):338-354
8. Gader PD, Khabou MA (1996) Automatic feature generation for handwritten digit recognition. IEEE Trans Pattern Anal Mach Intell 18(12):1256-1261
9. Garcia-Pedrajas N, Hervas-Martinez C, Munoz-Perez J (2003) COVNET: A cooperative coevolutionary model for evolving artificial neural networks. IEEE Trans Neural Netw 14(3): 575-596
10. Gross G, Galiana FD (1987) Short-term load forecasting. IEEE Proc 75:1558-1573
11. Ham FM, Kostanic I (2001) Principles of neurocomputing for science & engineering. McGraw-Hill, New York
12. Haykin S (1999) Neural network: A comprehensive foundation. Prentice Hall, Englewood Cliffs
13. Heng ETH, Srinivasan D, Liew AC (1988) Short term load forecasting using genetic algorithm and neural networks. In: Proceedings of the 1998 international conference on energy management and power delivery, vol 2, pp 576-581
14. Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor
15. Holmström L, Koistinen P, Laaksonen J, Oja E (1997) Neural and statistical classifiers-taxonomy and two case studies. IEEE Trans Neural Netw 8(1):5-17
16. Hsu CC, Chen CY (2003) Regional load forecasting in Taiwan-applications of artificial neural networks. Energy Convers Manage 44:1941-1949
17. Joines J, Houck C (1994) On the use of non-stationary penalty functions to solve constrained optimization problems with genetic algorithm. In: Proceedings of the 1994 international symposium evolutionary computation, Orlando, pp 579-584
18. Kecman V (2001) Learning and soft computing, support vector machines, neural networks and fuzzy logic models. The MIT Press, Cambridge
19. Lam HK, Leung FHF (2004) Stability analysis, synthesis and optimization of radial-basis-function neural-network based controller for nonlinear systems. In: Proceedings of the 30th Annual Conference of the IEEE Industrial Electronics Society, IECON, Busan, Korea, pp 2813-2818
20. Lam HK, Leung FHF (2006) Design and stabilization of sampled-data neural-network-based control systems. IEEE Trans Syst Man Cybern B Cybern 36(5):995-1005
21. Lam HK, Ling SH, Leung FHF, Tam PKS (2004) Function estimation using a neural-fuzzy network and an improved genetic algorithm. Int J Approx Reason 30(3):243-260
22. Leung FHF, Lam HK, Ling SH, Tam PKS (2003) Tuning of the structure and parameters of neural network using an improved genetic algorithm. IEEE Trans Neural Netw 14(1):79-88
23. Leung KF, Leung FHF, Lam HK, Ling SH (2004) On interpretation of graffiti digits and characters for eBooks: Neural-fuzzy network and genetic algorithm approach. IEEE Trans Ind. Electron 51(2):464-471
24. Liang RH, Cheng CC (2002) Short-term load forecasting by a neuro-fuzzy based approach. Energy Power Energy Syst 24:103-111
25. Ling SH, Leung FHF (2007) An improved genetic algorithm with average-bound crossover and wavelet mutation operations. Soft Comput 11(1):7-31
26. Ling SH, Leung FHF, Lam HK, Lee YS, Tam PKS (2003) A novel GA-based neural network for short-term load forecasting. IEEE Trans Ind Electron 50(4):793-799
27. Ling SH, Leung FHF, Wong LK, Lam HK (2005) Computational intelligence techniques for home electric load forecasting and balancing. Int J Comput Intell Appl 5(3):371-391
28. Lovell DR, Downs T, Tsoi AC (1997) An evaluation of the neocognitron. IEEE Trans Neural Netw 8(5):1090-1105
29. Mallat SG (1989) A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674-693
30. Michalewicz Z (1994) Genetic algorithm + data structures = evolution programs, 2nd extended edn. Springer, Berlin
31. Moller MF (1993) A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw 6(4):525-533
32. Momoh JA, Wang Y, Elfayoumy M (1997) Artificial neural network based load forecasting. In: Proceedings of the IEEE International Conference System, Man, and Cybernetics: Computational Cybernetics and Simulation, vol 4, pp 3443-3451
33. Perez CA, Salinas CA, Estévez PA, Valenzuela PM (2003) Genetic design of biologically inspired receptive fields for neural pattern recognition. IEEE Trans. Syst Man Cybern B Cybern 33(2):258-270
34. Pham DT, Karaboga D (2000) Intelligent optimization techniques, genetic algorithms, tabu search, simulated annealing and neural networks. Springer, Berlin
35. Saksornchai T, Lee WJ, Methaprayoon K, Liao JR, Ross RJ (2005) Improve the unit commitment scheduling by using the neural-network-based short-term load forecasting. IEEE Trans Ind App 41(1):169-179
36. Senjyu T, Takara H, Funabashi T (2002) One-hour-ahead load forecasting using neural network. IEEE Trans Power Syst 17(1):113-118
37. Srinivas M, Patnaik LM (1994) Genetic algorithms: A survey. IEEE Comput 27(6):17-26
38. Tan KC, Lim MH, Yao X, Wang LP (eds) Recent advances in simulated evolution and learning. World Scientific, Singapore
39. Taylor JW, Buizza R (2002) Neural network load forecasting with weather ensemble predictions. IEEE Trans Power Syst 17(4):626-632
40. Wang LP, Fu XJ (2005) Data mining with computational intelligence. Springer, Berlin
41. Widrow B, Lehr MA (1990) 30 years of adaptive neural networks: perceptron, madaline, and backpropagation. Proc IEEE 78(9):1415-1442
42. Yang KH, Zhu JJ, Wang BS, Zhao LL (2004) Design of short-term load forecasting model based on fuzzy neural networks. In: Proceedings of the 5th World Congress on Intelligent Control and Automation, vol 3, pp 15-19
43. Yao X (1999) Evolving artificial neural networks. Proc IEEE 87(9):1423-1447
44. Yao S, Wei CJ, He ZY (1996) Evolving wavelet neural networks for function approximation. Electron Lett 32(4):360-361
45. Zhang Q, Benveniste A (1992) Wavelet networks. IEEE Trans Neural Netw 3(6):889-898
46. Zhang B, Fu M, Yan H, Jabri MA (1997) Handwritten digit recognition by adaptive-subspace self-organizing map (ASSOM). IEEE Trans Neural Netw 10(4):939-945
47. Zhang J, Walter GG, Miao Y, Lee WWN (1995) Wavelet neural networks for function learning. IEEE Trans Signal Process 43(6):1485-1497
48. Zurada JM (1992) Introduction to artificial neural systems. West Info Access