-
3
-
-
84989245793
-
Reglas de despacho y operación del sistema eléctrico nacional
-
Centro Nacional de Control de Energía (CENACE) (2001) Reglas de despacho y operación del sistema eléctrico nacional, México
-
(2001)
México
-
-
-
4
-
-
51849142610
-
Short term wind speed forecasting in La Venta, Oaxaca, Mexico, using artificial neural networks
-
Cadenas E, Rivera W (2009) Short term wind speed forecasting in La Venta, Oaxaca, Mexico, using artificial neural networks. Renew Energy 34:274–278
-
(2009)
Renew Energy
, vol.34
, pp. 274-278
-
-
Cadenas, E.1
Rivera, W.2
-
5
-
-
59049092945
-
Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction
-
Salcedo-Sanz S, Pérez-Bellidoa AM, Ortiz-García EG, Portilla-Figueras A, Prieto L, Paredes D (2009) Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction. Renew Energy 34:1451–1457
-
(2009)
Renew Energy
, vol.34
, pp. 1451-1457
-
-
Salcedo-Sanz, S.1
Pérez-Bellidoa, A.M.2
Ortiz-García, E.G.3
Portilla-Figueras, A.4
Prieto, L.5
Paredes, D.6
-
6
-
-
73549100861
-
Analysis and forecasting of wind velocity in Chetumal, Quintana Roo, using the single exponential smoothing method
-
Cadenas E, Jaramillo OA, Rivera W (2010) Analysis and forecasting of wind velocity in Chetumal, Quintana Roo, using the single exponential smoothing method. Renew Energy 35:925–930
-
(2010)
Renew Energy
, vol.35
, pp. 925-930
-
-
Cadenas, E.1
Jaramillo, O.A.2
Rivera, W.3
-
7
-
-
77953137822
-
On comparing three artificial neural networks for wind speed forecasting
-
Li G, Shi J (2010) On comparing three artificial neural networks for wind speed forecasting. Appl Energy 87:2313–2320
-
(2010)
Appl Energy
, vol.87
, pp. 2313-2320
-
-
Li, G.1
Shi, J.2
-
8
-
-
77949570119
-
A hybrid statistical method to predict wind speed and wind power
-
Liu H, Tian H, Chen C, Li Y (2010) A hybrid statistical method to predict wind speed and wind power. Renew Energy 35:1857–1861
-
(2010)
Renew Energy
, vol.35
, pp. 1857-1861
-
-
Liu, H.1
Tian, H.2
Chen, C.3
Li, Y.4
-
9
-
-
77954315872
-
Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA–ANN model
-
Cadenas E, Rivera W (2010) Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA–ANN model. Renew Energy 35:2732–2738
-
(2010)
Renew Energy
, vol.35
, pp. 2732-2738
-
-
Cadenas, E.1
Rivera, W.2
-
10
-
-
79751505649
-
Bayesian adaptive combination of short-term wind speed forecasts from neural network models
-
Li G, Shi J, Zhou J (2011) Bayesian adaptive combination of short-term wind speed forecasts from neural network models. Renew Energy 36:352–359
-
(2011)
Renew Energy
, vol.36
, pp. 352-359
-
-
Li, G.1
Shi, J.2
Zhou, J.3
-
11
-
-
78149358777
-
Comprehensive evaluation of ARMA–GARCH(-M) approaches for modeling the mean and volatility of wind speed
-
Liu H, Erdem E, Shi J (2011) Comprehensive evaluation of ARMA–GARCH(-M) approaches for modeling the mean and volatility of wind speed. Appl Energy 88:724–732
-
(2011)
Appl Energy
, vol.88
, pp. 724-732
-
-
Liu, H.1
Erdem, E.2
Shi, J.3
-
12
-
-
79961127156
-
Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
-
Guo Z, Zhao W, Lu H, Wang J (2012) Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model. Renew Energy 37:241–249
-
(2012)
Renew Energy
, vol.37
, pp. 241-249
-
-
Guo, Z.1
Zhao, W.2
Lu, H.3
Wang, J.4
-
13
-
-
84862213628
-
Comparison of two new ARIMA–ANN and ARIMA–Kalman hybrid methods for wind speed prediction
-
Liu H, Tian H, Li Y (2012) Comparison of two new ARIMA–ANN and ARIMA–Kalman hybrid methods for wind speed prediction. Appl Energy 98:415–424
-
(2012)
Appl Energy
, vol.98
, pp. 415-424
-
-
Liu, H.1
Tian, H.2
Li, Y.3
-
14
-
-
84864827118
-
Wind speed and wind energy forecast through Kalman filtering of numerical weather prediction model output
-
Cassola F, Burlando M (2012) Wind speed and wind energy forecast through Kalman filtering of numerical weather prediction model output. Appl Energy 99:154–166
-
(2012)
Appl Energy
, vol.99
, pp. 154-166
-
-
Cassola, F.1
Burlando, M.2
-
15
-
-
84864797603
-
Performance analysis of four modified approaches for wind speed forecasting
-
Zhang W, Wu J, Wang J, Zhao W, Shen L (2012) Performance analysis of four modified approaches for wind speed forecasting. Appl Energy 99:324–333
-
(2012)
Appl Energy
, vol.99
, pp. 324-333
-
-
Zhang, W.1
Wu, J.2
Wang, J.3
Zhao, W.4
Shen, L.5
-
16
-
-
84863508830
-
A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks
-
Liu H, Chen C, Tian H, Li Y (2012) A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks. Renew Energy 48:545–556
-
(2012)
Renew Energy
, vol.48
, pp. 545-556
-
-
Liu, H.1
Chen, C.2
Tian, H.3
Li, Y.4
-
17
-
-
84865439917
-
A hybrid strategy of short term wind power prediction
-
Peng H, Liu F, Yang X (2013) A hybrid strategy of short term wind power prediction. Renew Energy 50:590–595
-
(2013)
Renew Energy
, vol.50
, pp. 590-595
-
-
Peng, H.1
Liu, F.2
Yang, X.3
-
18
-
-
84883355288
-
Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach
-
Chen K, Yu J (2014) Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach. Appl Energy 113:690–705
-
(2014)
Appl Energy
, vol.113
, pp. 690-705
-
-
Chen, K.1
Yu, J.2
-
19
-
-
77953358593
-
A novel wind speed modeling approach using atmospheric pressure observations and hidden Markov models
-
Hocaoğlu FO, Gerek ON, Kurban M (2010) A novel wind speed modeling approach using atmospheric pressure observations and hidden Markov models. J Wind Eng Ind Aerodyn 98:472–481
-
(2010)
J Wind Eng Ind Aerodyn
, vol.98
, pp. 472-481
-
-
Hocaoğlu, F.O.1
Gerek, O.N.2
Kurban, M.3
-
22
-
-
42249097152
-
Identification of multivariate outliers: a performance study
-
Filzmoser P (2005) Identification of multivariate outliers: a performance study. Aust J Stat 34:127–138
-
(2005)
Aust J Stat
, vol.34
, pp. 127-138
-
-
Filzmoser, P.1
-
23
-
-
84883083678
-
A time series-based approach for renewable energy modeling
-
Hocaoğlu FO, Karanfil F (2013) A time series-based approach for renewable energy modeling. Renew Sustain Energy Rev 28:214
-
(2013)
Renew Sustain Energy Rev
, vol.28
, pp. 214
-
-
Hocaoğlu, F.O.1
Karanfil, F.2
-
24
-
-
84986174723
-
Likelihood ratio statistics for autoregressive processes
-
Dickey DA, Fuller WA (1981) Likelihood ratio statistics for autoregressive processes. Econometrica 49:1057–1072
-
(1981)
Econometrica
, vol.49
, pp. 1057-1072
-
-
Dickey, D.A.1
Fuller, W.A.2
-
25
-
-
11244305511
-
NARMAX time series model prediction: feedforward and recurrent fuzzy neural network approaches
-
Gao Y, Er MJ (2005) NARMAX time series model prediction: feedforward and recurrent fuzzy neural network approaches. Fuzzy Sets Syst 150(2):331–350
-
(2005)
Fuzzy Sets Syst
, vol.150
, Issue.2
, pp. 331-350
-
-
Gao, Y.1
Er, M.J.2
-
26
-
-
67549122417
-
Neural networks: a comprehensive foundation by Simon Haykin
-
Kubat M (1999) Neural networks: a comprehensive foundation by Simon Haykin. Knowl Eng Rev 13:409–412
-
(1999)
Knowl Eng Rev
, vol.13
, pp. 409-412
-
-
Kubat, M.1
-
27
-
-
0032146239
-
Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences
-
Gardner M, Dorling S (1998) Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences. Atmos Environ 32:2627–2636
-
(1998)
Atmos Environ
, vol.32
, pp. 2627-2636
-
-
Gardner, M.1
Dorling, S.2
-
28
-
-
77950894862
-
The use of NARX neural networks to predict chaotic time series
-
Diaconescu E (2008) The use of NARX neural networks to predict chaotic time series. WSEAS Trans Comput Res 3(3):182–191
-
(2008)
WSEAS Trans Comput Res
, vol.3
, Issue.3
, pp. 182-191
-
-
Diaconescu, E.1
-
29
-
-
10244235219
-
An activation function adapting training algorithm for sigmoidal feedforward networks
-
Pravin C, Yogesh S (2004) An activation function adapting training algorithm for sigmoidal feedforward networks. Neurocomputing 61:429–437
-
(2004)
Neurocomputing
, vol.61
, pp. 429-437
-
-
Pravin, C.1
Yogesh, S.2
-
31
-
-
16444364474
-
Data division for developing neural networks applied to geotechnical engineering
-
Shahin MA, Maier HR, Jaksa MB (2004) Data division for developing neural networks applied to geotechnical engineering. J Comput Civil Eng ASCE 18(2):105–114
-
(2004)
J Comput Civil Eng ASCE
, vol.18
, Issue.2
, pp. 105-114
-
-
Shahin, M.A.1
Maier, H.R.2
Jaksa, M.B.3
|