메뉴 건너뛰기




Volumn 21, Issue 7, 2005, Pages 1096-1105

Neural networks for event extraction from time series: A back propagation algorithm approach

Author keywords

Back propagation; Neural network; Time series

Indexed keywords

BACKPROPAGATION; FINANCE; TIME SERIES ANALYSIS;

EID: 27544467089     PISSN: 0167739X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.future.2004.03.009     Document Type: Conference Paper
Times cited : (12)

References (20)
  • 1
    • 0000057581 scopus 로고
    • Predicting the future: A connectionist approach
    • A. Weigend, B. Huberman, D. Rumelhart, Predicting the future: a connectionist approach, Int. J. Neural Syst. 1 (3) (1990) 193-209.
    • (1990) Int. J. Neural Syst. , vol.1 , Issue.3 , pp. 193-209
    • Weigend, A.1    Huberman, B.2    Rumelhart, D.3
  • 3
    • 0030109788 scopus 로고    scopus 로고
    • Predicting sun spots using a layered perceptron neural network
    • Y.R. Park, T.J. Murray, C. Chen, Predicting sun spots using a layered perceptron neural network, IEEE Trans. Neural Networks 7 (2) (1996) 501-505.
    • (1996) IEEE Trans. Neural Networks , vol.7 , Issue.2 , pp. 501-505
    • Park, Y.R.1    Murray, T.J.2    Chen, C.3
  • 5
    • 0033097707 scopus 로고    scopus 로고
    • A comparison between neural network forecasting techniques case study: River flow forecasting
    • A.F. Atiya, S.M. El-Shoura, S.I. Shaheen, M.S. El-Sherif, A comparison between neural network forecasting techniques case study: river flow forecasting, IEEE Trans. Neural Networks 10 (2) (1999) 402-409.
    • (1999) IEEE Trans. Neural Networks , vol.10 , Issue.2 , pp. 402-409
    • Atiya, A.F.1    El-Shoura, S.M.2    Shaheen, S.I.3    El-Sherif, M.S.4
  • 10
    • 0001889304 scopus 로고    scopus 로고
    • Stock price prediction using prior knowledge and neural network
    • K. Kohara, Stock price prediction using prior knowledge and neural network, Intell. Syst. Account. Manage. 6 (1997) 11-22.
    • (1997) Intell. Syst. Account. Manage. , vol.6 , pp. 11-22
    • Kohara, K.1
  • 11
    • 0040098040 scopus 로고    scopus 로고
    • Forecasting unstable and nonstationary time series
    • C. Grillenzoni, Forecasting unstable and nonstationary time series, Int. J. Forecast. 14 (1998) 469-482.
    • (1998) Int. J. Forecast. , vol.14 , pp. 469-482
    • Grillenzoni, C.1
  • 12
    • 0020118274 scopus 로고
    • Neural networks and physical systems with emergent collective computational abilities
    • J. Hopfleld, Neural networks and physical systems with emergent collective computational abilities, Proc. Nat. Acad. Sci. 79 (8) (1982) 2554-2558.
    • (1982) Proc. Nat. Acad. Sci. , vol.79 , Issue.8 , pp. 2554-2558
    • Hopfleld, J.1
  • 14
    • 0012598275 scopus 로고    scopus 로고
    • Predicting US recessions with leading indicators via neural network models
    • Q. Min, Predicting US recessions with leading indicators via neural network models, Int. J. Forecast. 17 (2001) 383-401.
    • (2001) Int. J. Forecast. , vol.17 , pp. 383-401
    • Min, Q.1
  • 15
    • 0000646059 scopus 로고
    • Learning internal representation by error propagation
    • D.E. Rumelhart, J.L. Mc-Clelland, PDP Research Group (Eds.), MIT Press, Cambridge, MA
    • D.E. Rumelhart, G.E. Hinton, R.J. Williams, Learning internal representation by error propagation, in: D.E. Rumelhart, J.L. Mc-Clelland, PDP Research Group (Eds.), Parallel Distributed Processing, MIT Press, Cambridge, MA, 1986, pp. 318-362.
    • (1986) Parallel Distributed Processing , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 16
    • 0026221027 scopus 로고
    • An information criterion for optimum neural network selection
    • D.B. Fogel, An information criterion for optimum neural network selection, IEEE Trans. Neural Networks 2 (5) (1991) 490-497.
    • (1991) IEEE Trans. Neural Networks , vol.2 , Issue.5 , pp. 490-497
    • Fogel, D.B.1
  • 17
    • 0031126025 scopus 로고    scopus 로고
    • Fitting MA models to linear non-Gaussian random field using higher order cumumants
    • J. Tugnait, Fitting MA models to linear non-Gaussian random field using higher order cumumants, IEEE Trans. Signal Process. 45 (1997) 1045-1050.
    • (1997) IEEE Trans. Signal Process. , vol.45 , pp. 1045-1050
    • Tugnait, J.1
  • 19
    • 0025635525 scopus 로고
    • Connectionist nonparametric regression: Multilayer feed forward networks can learn arbitrary mappings
    • H. White, Connectionist nonparametric regression: multilayer feed forward networks can learn arbitrary mappings, Neural Networks 3 (1990) 535-550.
    • (1990) Neural Networks , vol.3 , pp. 535-550
    • White, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.