SCOPUS 정보 검색 플랫폼

Volumn 4132 LNCS - II, Issue , 2006, Pages 161-170

Analysis of fast input selection: Application in time series prediction

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; MATHEMATICAL MODELS; NEURAL NETWORKS; STRATEGIC PLANNING;

NON-LINEAR MODELS; PARSIMONIOUS; TIME SERIES PREDICTION;

TIME SERIES ANALYSIS;

EID: 33749819171 PISSN: 03029743 EISSN: 16113349 Source Type: Book Series
DOI: 10.1007/11840930_17 Document Type: Conference Paper

Times cited : (7)

References (9)

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- Weigend, A.S., Gershenfeld, N.A. (eds.): Addison-Wesley
- Weigend, A.S., Gershenfeld, N.A. (eds.): Time Series Prediction: Forecasting the Future and Understanding the Past. Addison-Wesley (1994)
- (1994) Time Series Prediction: Forecasting the Future and Understanding the Past

2
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- The elements of statistical learning - Data mining, inference and prediction
- Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning - Data Mining, Inference and Prediction. Springer Series in Statistics. (2001)
- (2001) Springer Series in Statistics
- Hastie, T.¹ Tibshirani, R.² Friedman, J.³

3
- 0003991665
- Chapman & Hall/CRC
- Efron, B., Tibshirani, R.J.: An Introduction to the Bootstrap. Chapman & Hall/CRC (1993)
- (1993) An Introduction to the Bootstrap
- Efron, B.¹ Tibshirani, R.J.²

4
- 25144459911
- Input selection for long-term prediction of time-series
- Tikka, J., Hollmén, J., Lendasse, A.: Input Selection for Long-Term Prediction of Time-Series. In: Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN 2005). 1002-1009
- Proceedings of the 8th International Work-conference on Artificial Neural Networks (IWANN 2005) , pp. 1002-1009
- Tikka, J.¹ Hollmén, J.² Lendasse, A.³

5
- 25144480349
- Direct and recursive prediction of time series using mutual information selection
- Ji, Y., Hao, J., Reyhani, N., Lendasse, A.: Direct and Recursive Prediction of Time Series Using Mutual Information Selection. In: Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN 2005). 1010-1017
- Proceedings of the 8th International Work-conference on Artificial Neural Networks (IWANN 2005) , pp. 1010-1017
- Ji, Y.¹ Hao, J.² Reyhani, N.³ Lendasse, A.⁴

6
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- Prentice-Hall.
- Ljung, L.: System Identification - Theory for the User. 2nd Edition. Prentice-Hall. (1999)
- (1999) System Identification - Theory for the User. 2nd Edition
- Ljung, L.¹

7
- 0024880831
- Multilayer feedforward networks are universal approximators
- Hornik, K., Stinchcombe, M., White, H.: Multilayer Feedforward Networks are Universal Approximators. Neural Networks. 2 (1989) 359-366
- (1989) Neural Networks , vol.2 , pp. 359-366
- Hornik, K.¹ Stinchcombe, M.² White, H.³

8
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- Oxford Press
- Bishop, C.: Neural Networks in Pattern Recognition. Oxford Press (1996)
- (1996) Neural Networks in Pattern Recognition
- Bishop, C.¹

9
- 0037442845
- Review and comparison of methods to study the contribution of variables in artificial neural network models
- Gevrey, M., Dimopoulos, I., Lek, S.: Review and Comparison of Methods to Study the Contribution of Variables in Artificial Neural Network Models. Ecological Modelling 160 (2003) 249-264
- (2003) Ecological Modelling , vol.160 , pp. 249-264
- Gevrey, M.¹ Dimopoulos, I.² Lek, S.³

* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.