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Volumn 299, Issue , 2015, Pages 99-116

A weighted LS-SVM based learning system for time series forecasting

Author keywords

Multi step forecasting; Mutual information; Nearest neighbor; Support vector machine; Time series forecasting

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION MAKING; LEARNING SYSTEMS; NEAREST NEIGHBOR SEARCH; SUPPORT VECTOR MACHINES; TIME SERIES;

EID: 84961292151     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.12.031     Document Type: Article
Times cited : (108)

References (72)
  • 1
    • 84961292008 scopus 로고    scopus 로고
    • A new hybrid enhanced local linear neuro-fuzzy model based on the optimized singular spectrum analysis and its application for nonlinear and chaotic time series forecasting
    • M. Abdollahzade, A. Miranian, H. Hassani, and H. Iranmanesh A new hybrid enhanced local linear neuro-fuzzy model based on the optimized singular spectrum analysis and its application for nonlinear and chaotic time series forecasting Inform. Sci. 295 2015 107 125
    • (2015) Inform. Sci. , vol.295 , pp. 107-125
    • Abdollahzade, M.1    Miranian, A.2    Hassani, H.3    Iranmanesh, H.4
  • 2
    • 84906836745 scopus 로고    scopus 로고
    • A homogeneous ensemble of artificial neural networks for time series forecasting
    • R. Adhikari, and R.K. Agrawal A homogeneous ensemble of artificial neural networks for time series forecasting Int. J. Comput. Appl. 32 7 2011 1 8
    • (2011) Int. J. Comput. Appl. , vol.32 , Issue.7 , pp. 1-8
    • Adhikari, R.1    Agrawal, R.K.2
  • 3
    • 0025725905 scopus 로고
    • Instance-based learning algorithms
    • D.W. Aha, D. Kibler, and M.K. Albert Instance-based learning algorithms Mach. Learn. 6 1 1991 37 66
    • (1991) Mach. Learn. , vol.6 , Issue.1 , pp. 37-66
    • Aha, D.W.1    Kibler, D.2    Albert, M.K.3
  • 4
    • 84906836531 scopus 로고    scopus 로고
    • ANN based prediction of blast furnace parameters
    • S.K. Bag ANN based prediction of blast furnace parameters Inst. Eng. 68 1 2007 37 42
    • (2007) Inst. Eng. , vol.68 , Issue.1 , pp. 37-42
    • Bag, S.K.1
  • 5
    • 84899582855 scopus 로고    scopus 로고
    • PSO-MISMO modeling strategy for multistep-ahead time series prediction
    • Y. Bao, T. Xiong, and Z. Hu PSO-MISMO modeling strategy for multistep-ahead time series prediction IEEE Trans. Cybernet. 44 5 2014 655 668
    • (2014) IEEE Trans. Cybernet. , vol.44 , Issue.5 , pp. 655-668
    • Bao, Y.1    Xiong, T.2    Hu, Z.3
  • 7
    • 84875389106 scopus 로고    scopus 로고
    • Mutual information-based inputs selection for electric load time series forecasting
    • M. Božić, M. Stojanović, Z. Stajić, and N. Floranović Mutual information-based inputs selection for electric load time series forecasting Entropy 15 2013 926 942
    • (2013) Entropy , vol.15 , pp. 926-942
    • Božić, M.1    Stojanović, M.2    Stajić, Z.3    Floranović, N.4
  • 8
    • 9244240793 scopus 로고    scopus 로고
    • Load forecasting using support vector machines: A study on EUNITE competition 2001
    • B.-J. Chen, M.-W. Chang, and C.-J. Lin Load forecasting using support vector machines: a study on EUNITE competition 2001 IEEE Trans. Power Syst. 19 4 2004 1821 1830
    • (2004) IEEE Trans. Power Syst. , vol.19 , Issue.4 , pp. 1821-1830
    • Chen, B.-J.1    Chang, M.-W.2    Lin, C.-J.3
  • 9
    • 79551645335 scopus 로고    scopus 로고
    • TAIEX forecasting based on fuzzy time series and fuzzy variation groups
    • S.-M. Chen TAIEX forecasting based on fuzzy time series and fuzzy variation groups IEEE Trans. Fuzzy Syst. 19 1 2011 1 12
    • (2011) IEEE Trans. Fuzzy Syst. , vol.19 , Issue.1 , pp. 1-12
    • Chen, S.-M.1
  • 10
    • 77957661892 scopus 로고    scopus 로고
    • Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques
    • S.-M. Chen, and Y.-C. Chang Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques Inform. Sci. 180 24 2010 4772 4783
    • (2010) Inform. Sci. , vol.180 , Issue.24 , pp. 4772-4783
    • Chen, S.-M.1    Chang, Y.-C.2
  • 11
    • 84867840221 scopus 로고    scopus 로고
    • TAIEX forecasting using fuzzy time series and automatically generated weighted of multiple factors
    • S.-M. Chen, H.-P. Chu, and T.-W. Sheu TAIEX forecasting using fuzzy time series and automatically generated weighted of multiple factors IEEE Trans. Syst. Man Cybernet. Part A 42 6 2012 1485 1495
    • (2012) IEEE Trans. Syst. Man Cybernet. Part A , vol.42 , Issue.6 , pp. 1485-1495
    • Chen, S.-M.1    Chu, H.-P.2    Sheu, T.-W.3
  • 12
    • 84890427180 scopus 로고    scopus 로고
    • Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques
    • S.-M. Chen, G.M.T. Manalu, J.-S. Pan, and H.-C. Liu Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques IEEE Trans. Cybernet. 43 3 2013 1102 1117
    • (2013) IEEE Trans. Cybernet. , vol.43 , Issue.3 , pp. 1102-1117
    • Chen, S.-M.1    Manalu, G.M.T.2    Pan, J.-S.3    Liu, H.-C.4
  • 13
    • 29444444293 scopus 로고    scopus 로고
    • Time-series prediction using a local linear wavelet neural network
    • Y. Chen, B. Yang, and J. Dong Time-series prediction using a local linear wavelet neural network Neurocomputing 69 4-6 2006 449 465
    • (2006) Neurocomputing , vol.69 , Issue.46 , pp. 449-465
    • Chen, Y.1    Yang, B.2    Dong, J.3
  • 14
    • 77952552084 scopus 로고    scopus 로고
    • Feature selection for time series prediction - A combined filter and wrapper approach for neural networks
    • S.F. Crone, and N. Kourentzes Feature selection for time series prediction - a combined filter and wrapper approach for neural networks Neurocomputing 73 10-12 2010 1923 1936
    • (2010) Neurocomputing , vol.73 , Issue.1012 , pp. 1923-1936
    • Crone, S.F.1    Kourentzes, N.2
  • 16
    • 84961336296 scopus 로고    scopus 로고
    • EUNITE Data Set. < http://neuron.tuke.sk/competition/index.php >.
    • EUNITE Data Set
  • 17
    • 36348930598 scopus 로고    scopus 로고
    • Toward estimating autonomous neural network-based electric load forecasters
    • V.H. Ferreira, and A.P. Alves da Silva Toward estimating autonomous neural network-based electric load forecasters IEEE Trans. Power Syst. 22 4 2007 1554 1562
    • (2007) IEEE Trans. Power Syst. , vol.22 , Issue.4 , pp. 1554-1562
    • Ferreira, V.H.1    Alves Da Silva, A.P.2
  • 18
    • 78149358308 scopus 로고    scopus 로고
    • Self-organizing multi-layer perceptron
    • B. Gas Self-organizing multi-layer perceptron IEEE Trans. Neural Netw. 21 11 2010 1766 1779
    • (2010) IEEE Trans. Neural Netw. , vol.21 , Issue.11 , pp. 1766-1779
    • Gas, B.1
  • 19
    • 84891745412 scopus 로고    scopus 로고
    • Interval type-2 fuzzy weight adjustment for backpropagation neural networks with application in time series prediction
    • F. Gaxiola, P. Melin, F. Valdez, and O. Castillo Interval type-2 fuzzy weight adjustment for backpropagation neural networks with application in time series prediction Inform. Sci. 260 2014 1 14
    • (2014) Inform. Sci. , vol.260 , pp. 1-14
    • Gaxiola, F.1    Melin, P.2    Valdez, F.3    Castillo, O.4
  • 20
    • 12144271359 scopus 로고    scopus 로고
    • A dynamic architecture for artificial neural networks
    • M. Ghiassi, and H. Saidane A dynamic architecture for artificial neural networks Neurocomputing 63 2005 397 413
    • (2005) Neurocomputing , vol.63 , pp. 397-413
    • Ghiassi, M.1    Saidane, H.2
  • 21
    • 33745952342 scopus 로고    scopus 로고
    • 25 years of time series forecasting
    • J. G De Gooijer, and R.J. Hyndman 25 years of time series forecasting Int. J. Forecast. 22 3 2006 443 473
    • (2006) Int. J. Forecast. , vol.22 , Issue.3 , pp. 443-473
    • De Gooijer, J.G.1    Hyndman, R.J.2
  • 22
    • 70350220741 scopus 로고    scopus 로고
    • A model updating strategy for predicting time series with seasonal patterns
    • J.A. Guajardo, R. Weber, and J. Miranda A model updating strategy for predicting time series with seasonal patterns Appl. Soft Comput. 10 1 2010 276 283
    • (2010) Appl. Soft Comput. , vol.10 , Issue.1 , pp. 276-283
    • Guajardo, J.A.1    Weber, R.2    Miranda, J.3
  • 23
    • 79953724824 scopus 로고    scopus 로고
    • Using artificial neural network models in stock market index prediction
    • E. Guresen, G. Kayakutlu, and T.U. Daim Using artificial neural network models in stock market index prediction Expert Syst. Appl. 38 8 2011 10389 10397
    • (2011) Expert Syst. Appl. , vol.38 , Issue.8 , pp. 10389-10397
    • Guresen, E.1    Kayakutlu, G.2    Daim, T.U.3
  • 27
    • 21644478686 scopus 로고    scopus 로고
    • Large neural networks for electricity load forecasting: Are they overfitted?
    • H.S. Hippert, D.W. Bunn, and R.C. Souza Large neural networks for electricity load forecasting: are they overfitted? Int. J. Forecast. 21 3 2005 425 434
    • (2005) Int. J. Forecast. , vol.21 , Issue.3 , pp. 425-434
    • Hippert, H.S.1    Bunn, D.W.2    Souza, R.C.3
  • 30
    • 84870983806 scopus 로고    scopus 로고
    • Long-term business cycle forecasting through a potential intuitionistic fuzzy least-squares support vector regression approach
    • K.-C. Hung, and K.-P. Lin Long-term business cycle forecasting through a potential intuitionistic fuzzy least-squares support vector regression approach Inform. Sci. 224 2013 37 48
    • (2013) Inform. Sci. , vol.224 , pp. 37-48
    • Hung, K.-C.1    Lin, K.-P.2
  • 32
    • 0027601884 scopus 로고
    • ANFIS: Adaptive-network based fuzzy inference systems
    • J.-S.R. Jang ANFIS: adaptive-network based fuzzy inference systems IEEE Trans. Syst. Man Cybernet. 23 3 1993 665 685
    • (1993) IEEE Trans. Syst. Man Cybernet. , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.-S.R.1
  • 33
    • 84899618956 scopus 로고    scopus 로고
    • Predicting dynamic deformation of retaining structure by LSSVR-based time series method
    • Z. Ji, B. Wang, S. Deng, and Z. You Predicting dynamic deformation of retaining structure by LSSVR-based time series method Neurocomputing 137 2014 165 172
    • (2014) Neurocomputing , vol.137 , pp. 165-172
    • Ji, Z.1    Wang, B.2    Deng, S.3    You, Z.4
  • 34
    • 77956789396 scopus 로고    scopus 로고
    • Application of improved local models of large scale database-based online modeling to prediction of molten iron temperature of blast furnace
    • N. Kaneko, S. Matsuzaki, M. Ito, H. Oogai, and K. Uchida Application of improved local models of large scale database-based online modeling to prediction of molten iron temperature of blast furnace ISIJ Int. 50 7 2010 939 945
    • (2010) ISIJ Int. , vol.50 , Issue.7 , pp. 939-945
    • Kaneko, N.1    Matsuzaki, S.2    Ito, M.3    Oogai, H.4    Uchida, K.5
  • 36
    • 70349453596 scopus 로고    scopus 로고
    • An artificial neural network (p, d, q) model for time series forecasting
    • M. Khashei, and M. Bijari An artificial neural network (p, d, q) model for time series forecasting Expert Syst. Appl. 37 1 2010 479 489
    • (2010) Expert Syst. Appl. , vol.37 , Issue.1 , pp. 479-489
    • Khashei, M.1    Bijari, M.2
  • 37
    • 84877283545 scopus 로고    scopus 로고
    • Which methodology is better for combining linear and nonlinear models for time series forecasting?
    • M. Khashei, and M. Bijari Which methodology is better for combining linear and nonlinear models for time series forecasting? J. Ind. Syst. Eng. 4 4 2011 265 285
    • (2011) J. Ind. Syst. Eng. , vol.4 , Issue.4 , pp. 265-285
    • Khashei, M.1    Bijari, M.2
  • 39
    • 61649090211 scopus 로고    scopus 로고
    • Short-term prediction of wind farm power: A data mining approach
    • A. Kusiak, H. Zheng, and Z. Song Short-term prediction of wind farm power: a data mining approach IEEE Trans. Energy Convers. 24 1 2009 125 136
    • (2009) IEEE Trans. Energy Convers. , vol.24 , Issue.1 , pp. 125-136
    • Kusiak, A.1    Zheng, H.2    Song, Z.3
  • 40
    • 84961304372 scopus 로고    scopus 로고
    • Laser Time Series Data Set. < http://www-psych.stanford.edu/andreas/Time-Series/SantaFe.html >.
    • Laser Time Series Data Set
  • 41
    • 0037525534 scopus 로고    scopus 로고
    • A neuro-fuzzy system modeling with self-constructing rule generation and hybrid SVD-based learning
    • S.-J. Lee, and C.-S. Ouyang A neuro-fuzzy system modeling with self-constructing rule generation and hybrid SVD-based learning IEEE Trans. Fuzzy Syst. 11 3 2003 341 353
    • (2003) IEEE Trans. Fuzzy Syst. , vol.11 , Issue.3 , pp. 341-353
    • Lee, S.-J.1    Ouyang, C.-S.2
  • 42
    • 0000702165 scopus 로고
    • Mutual information functions versus correlation functions
    • W. Li Mutual information functions versus correlation functions J. Stat. Phys. 60 5-6 1990 823 837
    • (1990) J. Stat. Phys. , vol.60 , Issue.56 , pp. 823-837
    • Li, W.1
  • 43
    • 84862806670 scopus 로고    scopus 로고
    • Application of type-2 neuro-fuzzy modeling in stock price prediction
    • C.-F. Liu, C.-Y. Yeh, and S.-J. Lee Application of type-2 neuro-fuzzy modeling in stock price prediction Appl. Soft Comput. 12 4 2012 1348 1358
    • (2012) Appl. Soft Comput. , vol.12 , Issue.4 , pp. 1348-1358
    • Liu, C.-F.1    Yeh, C.-Y.2    Lee, S.-J.3
  • 44
    • 84961321988 scopus 로고    scopus 로고
    • LS-SVM Program. < http://www.esat.kuleuven.be/sista/lssvmlab/ >.
    • LS-SVM Program
  • 47
    • 84898678160 scopus 로고    scopus 로고
    • Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction
    • A. Miranian, and M. Abdollahzade Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction IEEE Trans. Neural Netw. Learn. Syst. 24 2 2013 207 218
    • (2013) IEEE Trans. Neural Netw. Learn. Syst. , vol.24 , Issue.2 , pp. 207-218
    • Miranian, A.1    Abdollahzade, M.2
  • 51
    • 84961343419 scopus 로고    scopus 로고
    • Poland Data Set. < http://research.ics.aalto.fi/eiml/datasets.shtml >.
    • Poland Data Set..
  • 52
    • 66449136989 scopus 로고    scopus 로고
    • Time series prediction using support vector machines: A survey
    • N.I. Sapankevych, and R. Sankar Time series prediction using support vector machines: a survey IEEE Comput. Intell. Mag. 4 2 2009 24 38
    • (2009) IEEE Comput. Intell. Mag. , vol.4 , Issue.2 , pp. 24-38
    • Sapankevych, N.I.1    Sankar, R.2
  • 53
    • 2442474088 scopus 로고    scopus 로고
    • Time series forecasting with a hybrid clustering scheme and pattern recognition
    • A. Sfetsos, and C. Siriopoulos Time series forecasting with a hybrid clustering scheme and pattern recognition IEEE Trans. Syst. Man Cybernet. Part A 34 3 2004 399 405
    • (2004) IEEE Trans. Syst. Man Cybernet. Part A , vol.34 , Issue.3 , pp. 399-405
    • Sfetsos, A.1    Siriopoulos, C.2
  • 55
    • 0000173897 scopus 로고
    • Fuzzy time series and its models
    • O. Song, and B.S. Chissom Fuzzy time series and its models Fuzzy Sets Syst. 54 3 1993 269 277
    • (1993) Fuzzy Sets Syst. , vol.54 , Issue.3 , pp. 269-277
    • Song, O.1    Chissom, B.S.2
  • 56
    • 38149147511 scopus 로고
    • Forecasting enrollments with fuzzy time series - Part i
    • O. Song, and B.S. Chissom Forecasting enrollments with fuzzy time series - Part I Fuzzy Sets Syst. 54 1 1993 1 9
    • (1993) Fuzzy Sets Syst. , vol.54 , Issue.1 , pp. 1-9
    • Song, O.1    Chissom, B.S.2
  • 57
    • 38149146997 scopus 로고
    • Forecasting enrollments with fuzzy time series - Part II
    • O. Song, and B.S. Chissom Forecasting enrollments with fuzzy time series - Part II Fuzzy Sets Syst. 62 1 1994 1 8
    • (1994) Fuzzy Sets Syst. , vol.62 , Issue.1 , pp. 1-8
    • Song, O.1    Chissom, B.S.2
  • 58
    • 33646231252 scopus 로고    scopus 로고
    • Mutual information and k-nearest neighbors approximator for time series prediction
    • A. Sorjamaa, J. Hao, and A. Lendasse Mutual information and k-nearest neighbors approximator for time series prediction Lect. Notes Comput. Sci. 3657 2005 553 558
    • (2005) Lect. Notes Comput. Sci. , vol.3657 , pp. 553-558
    • Sorjamaa, A.1    Hao, J.2    Lendasse, A.3
  • 59
    • 34548170754 scopus 로고    scopus 로고
    • Methodology for long-term prediction of time series
    • A. Sorjamaa, J. Hao, N. Reyhani, Y. Ji, and A. Lendasse Methodology for long-term prediction of time series Neurocomputing 70 16-18 2007 2861 2869
    • (2007) Neurocomputing , vol.70 , Issue.1618 , pp. 2861-2869
    • Sorjamaa, A.1    Hao, J.2    Reyhani, N.3    Ji, Y.4    Lendasse, A.5
  • 62
    • 84901603905 scopus 로고    scopus 로고
    • A methodology for training set instance selection using mutual information in time series prediction
    • M.B. Stojanović, M.M. Božić, M.M. Stanković, and Z.P. Stajić A methodology for training set instance selection using mutual information in time series prediction Neurocomputing 141 2014 236 245
    • (2014) Neurocomputing , vol.141 , pp. 236-245
    • Stojanović, M.B.1    Božić, M.M.2    Stanković, M.M.3    Stajić, Z.P.4
  • 63
    • 84961382622 scopus 로고    scopus 로고
    • Sunspot Data Set. < http://sidc.oma.be/sunspot-data/ >.
    • Sunspot Data Set
  • 64
    • 0036825528 scopus 로고    scopus 로고
    • Weighted least squares support vector machines: Robustness and sparse approximation
    • J.A.K. Suykens, J. De Brabanter, L. Lukas, and J. Vandewalle Weighted least squares support vector machines: robustness and sparse approximation Neurocomputing 48 1-4 2002 85 105
    • (2002) Neurocomputing , vol.48 , Issue.14 , pp. 85-105
    • Suykens, J.A.K.1    De Brabanter, J.2    Lukas, L.3    Vandewalle, J.4
  • 66
    • 84961327479 scopus 로고    scopus 로고
    • TAIEX Web Site. < http://www.tese.com.tw/en/products/indices/tsec/taiex.php >.
    • TAIEX Web Site
  • 67
    • 84961357094 scopus 로고    scopus 로고
    • Modified support vector machines in financial time series forecasting
    • F.E.H. Tay, and L.J. Cao Modified support vector machines in financial time series forecasting Int. J. Forecast. 48 1 2002 69 84
    • (2002) Int. J. Forecast. , vol.48 , Issue.1 , pp. 69-84
    • Tay, F.E.H.1    Cao, L.J.2
  • 70
    • 0037243071 scopus 로고    scopus 로고
    • Time series forecasting using a hybrid ARIMA and neural network model
    • G.P. Zhang Time series forecasting using a hybrid ARIMA and neural network model Neurocomputing 50 2003 159 175
    • (2003) Neurocomputing , vol.50 , pp. 159-175
    • Zhang, G.P.1
  • 71
    • 84867884437 scopus 로고    scopus 로고
    • Iterated time series prediction with multiple support vector regression models
    • L. Zhang, W.-D. Zhou, P.-C. Chang, J.-W. Yang, and F.-Z. Li Iterated time series prediction with multiple support vector regression models Neurocomputing 99 2013 411 422
    • (2013) Neurocomputing , vol.99 , pp. 411-422
    • Zhang, L.1    Zhou, W.-D.2    Chang, P.-C.3    Yang, J.-W.4    Li, F.-Z.5
  • 72
    • 0742271676 scopus 로고    scopus 로고
    • Combining time series models for forecasting
    • H. Zou, and Y. Yang Combining time series models for forecasting Int. J. Forecast. 20 1 2004 69 84
    • (2004) Int. J. Forecast. , vol.20 , Issue.1 , pp. 69-84
    • Zou, H.1    Yang, Y.2


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