메뉴 건너뛰기




Volumn 177, Issue 24, 2007, Pages 5775-5797

Locally recurrent neural networks for wind speed prediction using spatial correlation

Author keywords

Adjoint models; Local recurrent neural networks; Recursive prediction error algorithm; Spatial correlation; Wind speed forecasting

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; CORRELATION METHODS; LEARNING SYSTEMS; ONLINE SYSTEMS; PERSONNEL TRAINING; REMOTE SENSING; WIND EFFECTS;

EID: 34648852323     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2007.05.024     Document Type: Article
Times cited : (176)

References (42)
  • 1
    • 33144481671 scopus 로고    scopus 로고
    • A stable neural network-based observer with application to flexible-joint manipulators
    • Abdollahi F., Talebi H.A., and Patel R.V. A stable neural network-based observer with application to flexible-joint manipulators. IEEE Trans. Neural Networks 17 1 (2006) 118-129
    • (2006) IEEE Trans. Neural Networks , vol.17 , Issue.1 , pp. 118-129
    • Abdollahi, F.1    Talebi, H.A.2    Patel, R.V.3
  • 3
    • 0000029787 scopus 로고
    • FIR and IIR synapses, a new neural network architecture for time series modeling
    • Back A.D., and Tsoi A.C. FIR and IIR synapses, a new neural network architecture for time series modeling. Neural Comput. 3 (1991) 375-385
    • (1991) Neural Comput. , vol.3 , pp. 375-385
    • Back, A.D.1    Tsoi, A.C.2
  • 5
    • 29444457388 scopus 로고    scopus 로고
    • Locally recurrent neural networks for long-term wind speed and power prediction
    • Barbounis T.G., and Theocharis J.B. Locally recurrent neural networks for long-term wind speed and power prediction. Neurocomputing 69 4-6 (2006) 466-496
    • (2006) Neurocomputing , vol.69 , Issue.4-6 , pp. 466-496
    • Barbounis, T.G.1    Theocharis, J.B.2
  • 6
    • 33750122966 scopus 로고    scopus 로고
    • T.G. Barbounis, J.B. Theocharis, Locally recurrent neural networks optimal filtering algorithms: application to wind speed prediction using spatial correlation, in: Proc. IEEE International Joint Conf. Neural Networks, 2005, pp. 2711-2716.
  • 7
    • 33847369874 scopus 로고    scopus 로고
    • A locally recurrent fuzzy neural network with application to the wind speed prediction using spatial correlation
    • Barbounis T.G., and Theocharis J.B. A locally recurrent fuzzy neural network with application to the wind speed prediction using spatial correlation. Neurocomputing 70 7-9 (2007) 525-1542
    • (2007) Neurocomputing , vol.70 , Issue.7-9 , pp. 525-1542
    • Barbounis, T.G.1    Theocharis, J.B.2
  • 8
    • 0027575091 scopus 로고
    • Power fluctuations in spatially dispersed wind turbine systems
    • Beyer H.G., Luther J., and Steinbergerwillms R. Power fluctuations in spatially dispersed wind turbine systems. Sol. Energy 64 4 (1993) 297-305
    • (1993) Sol. Energy , vol.64 , Issue.4 , pp. 297-305
    • Beyer, H.G.1    Luther, J.2    Steinbergerwillms, R.3
  • 11
    • 0017552781 scopus 로고
    • Variance analysis of wind characteristics for energy conversion
    • Corotis R., Sigl A., and Cohen M. Variance analysis of wind characteristics for energy conversion. J. Appl. Meteorol. 16 (1977) 1149-1157
    • (1977) J. Appl. Meteorol. , vol.16 , pp. 1149-1157
    • Corotis, R.1    Sigl, A.2    Cohen, M.3
  • 12
    • 2942570109 scopus 로고    scopus 로고
    • A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation
    • Damousis I.G., Alexiadis M.C., Theocharis J.B., and Dokopoulos P.S. A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation. IEEE Trans. Energy Convers. 19 2 (2004) 352-361
    • (2004) IEEE Trans. Energy Convers. , vol.19 , Issue.2 , pp. 352-361
    • Damousis, I.G.1    Alexiadis, M.C.2    Theocharis, J.B.3    Dokopoulos, P.S.4
  • 13
    • 0025841187 scopus 로고
    • Stochastic simulation and forecasting of hourly average wind speed sequences in Jamaica
    • Daniel A.R., and Chen A.A. Stochastic simulation and forecasting of hourly average wind speed sequences in Jamaica. Sol. Energy 46 (1991) 1-11
    • (1991) Sol. Energy , vol.46 , pp. 1-11
    • Daniel, A.R.1    Chen, A.A.2
  • 14
    • 0001657855 scopus 로고
    • Local feedback multilayered networks
    • Frasconi P., Gori M., and Soda G. Local feedback multilayered networks. Neural Comput. 4 (1992) 120-130
    • (1992) Neural Comput. , vol.4 , pp. 120-130
    • Frasconi, P.1    Gori, M.2    Soda, G.3
  • 15
    • 9744257846 scopus 로고    scopus 로고
    • Prediction of chaotic series based on recurrent predictor neural network
    • Han M., Xi J., Xu S., and Yin F.-L. Prediction of chaotic series based on recurrent predictor neural network. IEEE Trans. Signal Process. 52 12 (2004) 309-3416
    • (2004) IEEE Trans. Signal Process. , vol.52 , Issue.12 , pp. 309-3416
    • Han, M.1    Xi, J.2    Xu, S.3    Yin, F.-L.4
  • 16
    • 33646496168 scopus 로고    scopus 로고
    • Design and performance of an intelligent predictive controller for a six-degree-of-freedom robot using the Elman network
    • Koker R. Design and performance of an intelligent predictive controller for a six-degree-of-freedom robot using the Elman network. Inform. Sci. 176 12 (2006) 1781-1799
    • (2006) Inform. Sci. , vol.176 , Issue.12 , pp. 1781-1799
    • Koker, R.1
  • 17
    • 0029207879 scopus 로고
    • Diagonal recurrent neural networks for dynamic systems control
    • Ku C.C., and Lee K.Y. Diagonal recurrent neural networks for dynamic systems control. IEEE Trans. Neural Networks 6 (1995) 144-156
    • (1995) IEEE Trans. Neural Networks , vol.6 , pp. 144-156
    • Ku, C.C.1    Lee, K.Y.2
  • 18
    • 29244473883 scopus 로고    scopus 로고
    • Recurrent neural network based adaptive backstepping control for induction servomotors
    • Lin C.M., and Hsu C.-F. Recurrent neural network based adaptive backstepping control for induction servomotors. IEEE Trans. Indus. Electron. 52 6 (2005) 1677-1684
    • (2005) IEEE Trans. Indus. Electron. , vol.52 , Issue.6 , pp. 1677-1684
    • Lin, C.M.1    Hsu, C.-F.2
  • 19
    • 33646241633 scopus 로고    scopus 로고
    • Learning long-term dependences in NARX recurrent neural networks
    • Lin T., Horne B.G., Tino P., and Giles C.L. Learning long-term dependences in NARX recurrent neural networks. IEEE Trans. Neural Networks 7 (1996) 1329-1338
    • (1996) IEEE Trans. Neural Networks , vol.7 , pp. 1329-1338
    • Lin, T.1    Horne, B.G.2    Tino, P.3    Giles, C.L.4
  • 21
    • 33646903070 scopus 로고    scopus 로고
    • Adaptive feedback linearization control of chaotic systems via recurrent high-order neural networks
    • Lu Z., Shieh L.-S., Chen G., and Coleman N.P. Adaptive feedback linearization control of chaotic systems via recurrent high-order neural networks. Inform. Sci. 176 16 (2006) 2337-2354
    • (2006) Inform. Sci. , vol.176 , Issue.16 , pp. 2337-2354
    • Lu, Z.1    Shieh, L.-S.2    Chen, G.3    Coleman, N.P.4
  • 22
    • 0033751613 scopus 로고    scopus 로고
    • On the choice of parameters of the cost function in Nested modular RNN's
    • Mandic D.P., and Chambers J.A. On the choice of parameters of the cost function in Nested modular RNN's. IEEE Trans. Neural Networks 11 (2000) 315-322
    • (2000) IEEE Trans. Neural Networks , vol.11 , pp. 315-322
    • Mandic, D.P.1    Chambers, J.A.2
  • 23
    • 34648824921 scopus 로고    scopus 로고
    • M.B. Mathews, Neural network nonlinear adaptive filtering using the extended Kalman filter, in: Proc Int. Conf. Neural Networks, vol. I, 1990, pp. 115-119.
  • 24
    • 33748205931 scopus 로고    scopus 로고
    • Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons
    • Oh S.-K., Pedrycz W., and Roh S.-B. Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons. Inform. Sci. 176 (2006) 3490-3519
    • (2006) Inform. Sci. , vol.176 , pp. 3490-3519
    • Oh, S.-K.1    Pedrycz, W.2    Roh, S.-B.3
  • 25
    • 33144477025 scopus 로고    scopus 로고
    • Genetically optimized fuzzy polynomial neural networks
    • Oh S.-K., Pedrycz W., and Park H.-S. Genetically optimized fuzzy polynomial neural networks. IEEE Trans. Fuzzy Syst. 14 1 (2006) 125-144
    • (2006) IEEE Trans. Fuzzy Syst. , vol.14 , Issue.1 , pp. 125-144
    • Oh, S.-K.1    Pedrycz, W.2    Park, H.-S.3
  • 26
    • 0742320761 scopus 로고    scopus 로고
    • Self-organizing polynomial neural networks based on polynomial and fuzzy polynomial neurons
    • Oh S.-K., and Pedrycz W. Self-organizing polynomial neural networks based on polynomial and fuzzy polynomial neurons. Fuzzy Sets Syst. 142 2 (2004) 163-198
    • (2004) Fuzzy Sets Syst. , vol.142 , Issue.2 , pp. 163-198
    • Oh, S.-K.1    Pedrycz, W.2
  • 27
    • 33746351754 scopus 로고    scopus 로고
    • The design of self-organizing neural networks based on PN's and FPN's with the aid of genetic optimization and extended GMDH method
    • Oh S.-K., and Pedrycz W. The design of self-organizing neural networks based on PN's and FPN's with the aid of genetic optimization and extended GMDH method. Int. J. Approx. Reason. 43 1 (2006) 26-58
    • (2006) Int. J. Approx. Reason. , vol.43 , Issue.1 , pp. 26-58
    • Oh, S.-K.1    Pedrycz, W.2
  • 28
    • 0029155266 scopus 로고
    • A simple method for spatial interpolation of the wind in complex terrain
    • Palomino I., and Martin F. A simple method for spatial interpolation of the wind in complex terrain. J. Appl. Meteorol. 34 7 (1995) 1678-1693
    • (1995) J. Appl. Meteorol. , vol.34 , Issue.7 , pp. 1678-1693
    • Palomino, I.1    Martin, F.2
  • 29
    • 0028401031 scopus 로고
    • Neurocontrol of nonlinear dynamical systems with Kalman filter-trained recurrent networks
    • Puskorius G.V., and Feldkamp L.A. Neurocontrol of nonlinear dynamical systems with Kalman filter-trained recurrent networks. IEEE Trans. Neural Networks 5 (1994) 279-297
    • (1994) IEEE Trans. Neural Networks , vol.5 , pp. 279-297
    • Puskorius, G.V.1    Feldkamp, L.A.2
  • 31
    • 0021976240 scopus 로고
    • Wind array power prediction for improved operating economics and reliability
    • Schlueter R.A., Sigari G., and Costi A. Wind array power prediction for improved operating economics and reliability. IEEE Trans. Power Appl. Syst. 104 (1985) 137-142
    • (1985) IEEE Trans. Power Appl. Syst. , vol.104 , pp. 137-142
    • Schlueter, R.A.1    Sigari, G.2    Costi, A.3
  • 32
    • 0028392484 scopus 로고
    • Back propagation through adjoints for the identification of nonlinear dynamic systems using recurrent neural models
    • Srinivasan B., Prasad U.R., and Rao N.J. Back propagation through adjoints for the identification of nonlinear dynamic systems using recurrent neural models. IEEE Trans. Neural Networks 10 2 (1994) 213-228
    • (1994) IEEE Trans. Neural Networks , vol.10 , Issue.2 , pp. 213-228
    • Srinivasan, B.1    Prasad, U.R.2    Rao, N.J.3
  • 33
    • 0028392406 scopus 로고
    • Locally recurrent globally feedforward networks: a critical review of architectures
    • Tsoi A.C., and Back A.D. Locally recurrent globally feedforward networks: a critical review of architectures. IEEE Trans. Neural Networks 5 (1994) 229-239
    • (1994) IEEE Trans. Neural Networks , vol.5 , pp. 229-239
    • Tsoi, A.C.1    Back, A.D.2
  • 34
    • 0242523780 scopus 로고    scopus 로고
    • Nonlinear system identification using discrete-time recurrent neural networks with stable learning algorithms
    • Yu W. Nonlinear system identification using discrete-time recurrent neural networks with stable learning algorithms. Inform. Sci. 158 (2004) 131-147
    • (2004) Inform. Sci. , vol.158 , pp. 131-147
    • Yu, W.1
  • 36
    • 0025555891 scopus 로고    scopus 로고
    • E.A. Wan, Temporal backpropagation for FIR neural networks, in: Proc. Int. Joint Conf. Neural Networks, vol. 1, 1990, pp. 575-580.
  • 37
    • 0001317823 scopus 로고    scopus 로고
    • Diagrammatic derivation of gradient algorithms for neural networks
    • Wan E.A., and Beaufais F. Diagrammatic derivation of gradient algorithms for neural networks. Neural Comput. 8 (1996) 182-201
    • (1996) Neural Comput. , vol.8 , pp. 182-201
    • Wan, E.A.1    Beaufais, F.2
  • 38
    • 33747081982 scopus 로고    scopus 로고
    • A fully automated recurrent neural network for unknown dynamic system identification and control
    • Wang J.-S., and Chen Y.-P. A fully automated recurrent neural network for unknown dynamic system identification and control. IEEE Trans. Circ. Syst. I: Regular Papers 53 6 (2006) 1363-1372
    • (2006) IEEE Trans. Circ. Syst. I: Regular Papers , vol.53 , Issue.6 , pp. 1363-1372
    • Wang, J.-S.1    Chen, Y.-P.2
  • 39
    • 34648816439 scopus 로고    scopus 로고
    • P.J. Werbos, Beyond regression: new tools for prediction and analysis in the behavioral sciences, Ph.D. dissertation, Committee on Appl. Math., Harvard Univ., Cambridge, MA, 1974.
  • 40
    • 0001609567 scopus 로고
    • An efficient gradient-based algorithm for on-line training of recurrent network trajectories
    • Williams R.J., and Peng J. An efficient gradient-based algorithm for on-line training of recurrent network trajectories. Neural Comput. 2 (1990) 490-501
    • (1990) Neural Comput. , vol.2 , pp. 490-501
    • Williams, R.J.1    Peng, J.2
  • 41
    • 0001202594 scopus 로고
    • A learning algorithm for continually running fully recurrent neural networks
    • Williams R.J., and Zipser D. A learning algorithm for continually running fully recurrent neural networks. Neural Comput. 1 (1989) 270-280
    • (1989) Neural Comput. , vol.1 , pp. 270-280
    • Williams, R.J.1    Zipser, D.2
  • 42
    • 34648836621 scopus 로고    scopus 로고
    • R. Williams, Training recurrent networks using the extended Kalman filter, in: International Joint Conf. on Neural Networks, Baltimore, vol. IV, 1992, pp. 241-246.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.