메뉴 건너뛰기




Volumn 4, Issue , 2003, Pages 2314-2321

Financial forecasting through unsupervised clustering and evolutionary trained neural networks

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS; TIME SERIES ANALYSIS;

EID: 70349406797     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2003.1299377     Document Type: Conference Paper
Times cited : (34)

References (19)
  • 1
    • 84867932186 scopus 로고    scopus 로고
    • Exchange-rates forecasting: A hybrid algorithm based on genetically optimized adaptive neural networks
    • A. S. Andreou, E. F. Georgopoulos, and S. D Likothanassis, Exchange-rates forecasting: A hybrid algorithm based on genetically optimized adaptive neural networks. Computational Economics 20(2002), 191-210.
    • (2002) Computational Economics , vol.20 , pp. 191-210
    • Andreou, A.S.1    Georgopoulos, E.F.2    Likothanassis, S.D.3
  • 2
    • 0036464756 scopus 로고    scopus 로고
    • The particle swarmexplosion, stability, and convergence in a multidimensional complex space
    • M. Clerc and J. Kennedy, The particle swarmexplosion, stability, and convergence in a multidimensional complex space, IEEE Trans. Evol. Compul. 6(2002), no. 1. 58-73.
    • (2002) IEEE Trans. Evol. Compul. , vol.6 , Issue.1 , pp. 58-73
    • Clerc, M.1    Kennedy, J.2
  • 5
    • 0035399722 scopus 로고    scopus 로고
    • Noisy time series prediction using a recurrent neural network and grammatical inference
    • L. C. Giles., S. Lawrence, and A. H. Tsoi, Noisy time series prediction using a recurrent neural network and grammatical inference, Machine Learning 44(2001), no. 1/2, 161-183.
    • (2001) Machine Learning , vol.44 , Issue.1-2 , pp. 161-183
    • Giles, L.C.1    Lawrence, S.2    Tsoi, A.H.3
  • 7
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K. Hornik, Multilayer feedforward networks are universal approximators. Neural Networks 2(1989), 359-366.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1
  • 8
    • 35949006791 scopus 로고
    • Determining embedding dimension for phase-space reconstruction using a geometrical construction
    • M. B. Kennel, R. Brown, and H. D. Abarbanel, Determining embedding dimension for phase-space reconstruction using a geometrical construction. Physical Review A 45(1992), no. 6, 3403-3411.
    • (1992) Physical Review A , vol.45 , Issue.6 , pp. 3403-3411
    • Kennel, M.B.1    Brown, R.2    Abarbanel, H.D.3
  • 10
    • 0344291226 scopus 로고    scopus 로고
    • Recent approaches to global optimization problems through particle swarm optimization
    • K. E. Parsopoulos and M. N. Vrahatis, Recent approaches to global optimization problems through particle swarm optimization. Natural Computing 1(2002), no. 2-3, 235-306.
    • (2002) Natural Computing , vol.1 , Issue.2-3 , pp. 235-306
    • Parsopoulos, K.E.1    Vrahatis, M.N.2
  • 11
    • 85011438572 scopus 로고    scopus 로고
    • Approximation theory of the mlp model in neural networks
    • A. Pinkus, Approximation theory of the mlp model in neural networks, Acta Numerica (1999). 143-195.
    • (1999) Acta Numerica , pp. 143-195
    • Pinkus, A.1
  • 12
    • 4043139159 scopus 로고    scopus 로고
    • Parallel evolutionary training algorithms for 'hardware-friendly' neural networks
    • V. P. Plagianakos and M. N. Vrahatis, Parallel evolutionary training algorithms for 'hardware-friendly' neural networks. Natural Computing 1(2002), 307-322.
    • (2002) Natural Computing , vol.1 , pp. 307-322
    • Plagianakos, V.P.1    Vrahatis, M.N.2
  • 14
    • 0142000477 scopus 로고    scopus 로고
    • Differential evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces
    • R. Storn and K. Price, Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces. Journal of Global Optimization 11(1997), 341-359.
    • (1997) Journal of Global Optimization , vol.11 , pp. 341-359
    • Storn, R.1    Price, K.2
  • 15
    • 0000779360 scopus 로고
    • Detecting strange attractors in turbulence, dynamical systems and turbulence
    • D. A. Rand and L. S. Young, eds., Springer
    • F. Takens, Detecting strange attractors in turbulence, Dynamical Systems and Turbulence (D. A. Rand and L. S. Young, eds.), Lecture Notes in Mathematics, vol. 898, Springer, 1981, pp. 366-381.
    • (1981) Lecture Notes in Mathematics , vol.898 , pp. 366-381
    • Takens, F.1
  • 16
    • 0036230457 scopus 로고    scopus 로고
    • The new k-windows algorithm for improving the k-means clustering algorithm
    • M. N. Vrahatis, B. Boutsinas, P. Alevizos, and G. Pavlides, The new k-windows algorithm for improving the k-means clustering algorithm, Journal of Complexity 18(2002), 375-391.
    • (2002) Journal of Complexity , vol.18 , pp. 375-391
    • Vrahatis, M.N.1    Boutsinas, B.2    Alevizos, P.3    Pavlides, G.4
  • 17
    • 0034894378 scopus 로고    scopus 로고
    • An empirical analysis of data requirements for financial forecasting with neural networks
    • S. Walczak, An empirical analysis of data requirements for financial forecasting with neural networks, Journal of Management Information Systems 17(2001), no. 4, 203-222.
    • (2001) Journal of Management Information Systems , vol.17 , Issue.4 , pp. 203-222
    • Walczak, S.1
  • 18
    • 0025635525 scopus 로고
    • Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings
    • H. White, Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings, Neural Networks 3(1990), 535-549.
    • (1990) Neural Networks , vol.3 , pp. 535-549
    • White, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.