-
1
-
-
0000581356
-
An introduction to kernel and nearest-neighbor nonparametric regression
-
Altman, N.S.: An introduction to kernel and nearest-neighbor nonparametric regression. Am. Stat. 46(3), 175-185 (1992)
-
(1992)
Am. Stat
, vol.46
, Issue.3
, pp. 175-185
-
-
Altman, N.S.1
-
2
-
-
70049096782
-
Online short-term solar power forecasting. Sol
-
Bacher, P., Madsen, H., Nielsen, H.A.: Online short-term solar power forecasting. Sol. Energy 83(10), 1772-1783 (2009)
-
(2009)
Energy
, vol.83
, Issue.10
, pp. 1772-1783
-
-
Bacher, P.1
Madsen, H.2
Nielsen, H.A.3
-
3
-
-
0035478854
-
Random forests
-
Breiman, L.: Random forests. Mach. Learn. 45(1), 5-32 (2001)
-
(2001)
Mach. Learn
, vol.45
, Issue.1
, pp. 5-32
-
-
Breiman, L.1
-
4
-
-
0003802343
-
-
Taylor & Francis
-
Breiman, L., Friedman, J., Stone, C., Olshen, R.A.: Classification and regression trees. Taylor & Francis (1984)
-
(1984)
Classification and regression trees
-
-
Breiman, L.1
Friedman, J.2
Stone, C.3
Olshen, R.A.4
-
5
-
-
84874963419
-
Not all about consumption
-
Davidson, D.J., Andrews, J.: Not all about consumption. Science 339(6125), 1286-1287 (2013)
-
(2013)
Science
, vol.339
, Issue.6125
, pp. 1286-1287
-
-
Davidson, D.J.1
Andrews, J.2
-
6
-
-
0035470889
-
Greedy function approximation: A gradient boostingmachine
-
Friedman, J.H.: Greedy function approximation: a gradient boostingmachine.Ann. Stat. 1189-1232 (2001)
-
(2001)
Ann. Stat
, pp. 1189-1232
-
-
Friedman, J.H.1
-
9
-
-
29244490433
-
-
United Nations Development Programme, Bureau for Development Policy
-
Goldemberg, J., Johansson, T.B., Anderson, D.: World energy assessment: overview: 2004 Update. United Nations Development Programme, Bureau for Development Policy (2004)
-
(2004)
World Energy Assessment: Overview: 2004 Update
-
-
Goldemberg, J.1
Johansson, T.B.2
Erson, D.3
-
10
-
-
84942484786
-
Ridge regression: Biased estimation for nonorthogonal problems
-
Hoerl, A.E., Kennard, R.W.: Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12(1), 55-67 (1970)
-
(1970)
Technometrics
, vol.12
, Issue.1
, pp. 55-67
-
-
Hoerl, A.E.1
Kennard, R.W.2
-
11
-
-
84905712105
-
Energy forecasting: Past, present, and future. Foresight:
-
Hong, T.: Energy forecasting: past, present, and future. Foresight: Int. J. Appl. Forecast.Winter 2014, 43-48 (2014)
-
(2014)
Int. J. Appl. Forecast.Winter
, vol.2014
, pp. 43-48
-
-
Hong, T.1
-
12
-
-
84977662886
-
Hybrid prediction method for solar power using different computational intelligence algorithms. Smart Grid renew
-
Hossain, M.R., Oo, A.M.T., Shawkat Ali, A.B.M.: Hybrid prediction method for solar power using different computational intelligence algorithms. Smart Grid renew. Energy 4(1), 76-87 (2013)
-
(2013)
Energy
, vol.4
, Issue.1
, pp. 76-87
-
-
Hossain, M.R.1
Oo, A.2
Shawkat Ali, A.3
-
13
-
-
78751519285
-
Comparative study of power forecasting methods for PV stations
-
IEEE
-
Huang, Y., Lu, J., Liu, C., Xu, X. ,Wang, W., Zhou, X.: Comparative study of power forecasting methods for PV stations. In: Proceedings of the 2010 IEEE International Conference on Power System Technology (POWERCON), pp. 1-6. IEEE (2010)
-
(2010)
Proceedings of the 2010 IEEE International Conference on Power System Technology (POWERCON)
, pp. 1-6
-
-
Huang, Y.1
Lu, J.2
Liu, C.3
Xu, X.4
Wang, W.5
Zhou, X.6
-
16
-
-
84899493943
-
Probabilistic forecasts of solar irradiance using stochastic differential equations
-
Iversen, E.B., Morales, J.M., Møller, J.K., Madsen, H.: Probabilistic forecasts of solar irradiance using stochastic differential equations. Environmetrics 25(3), 152-164 (2014)
-
(2014)
Environmetrics
, vol.25
, Issue.3
, pp. 152-164
-
-
Iversen, E.B.1
Morales, J.M.2
Møller, J.K.3
Madsen, H.4
-
17
-
-
84925105967
-
-
Cambridge University Press, New York
-
Koenker, R.: Quantile Regression. Cambridge University Press, New York (2005)
-
(2005)
Quantile Regression
-
-
Koenker, R.1
-
19
-
-
79954613949
-
Forecasting of global and direct solar irradiance using stochastic learning methods, ground experiments and the NWS database
-
Marquez, R., Coimbra, C.F.M.: Forecasting of global and direct solar irradiance using stochastic learning methods, ground experiments and the NWS database. Sol. Energy 85(5), 746-756 (2011)
-
(2011)
Sol. Energy
, vol.85
, Issue.5
, pp. 746-756
-
-
Marquez, R.1
Coimbra, C.2
-
20
-
-
84912559024
-
Machine learning techniques for supporting renewable energy generation and integration: A survey
-
Perera, K.S., Aung, Z., Woon, W.L.: Machine learning techniques for supporting renewable energy generation and integration: a survey. In: Data Analytics for Renewable Energy Integration—Second ECML PKDD Workshop, DARE 2014, Lecture Notes in Computer Science, vol. 8817, pp. 81-96 (2014)
-
(2014)
Data Analytics for Renewable Energy Integration—Second ECML PKDD Workshop, DARE 2014, Lecture Notes in Computer Science
, vol.8817
, pp. 81-96
-
-
Perera, K.S.1
Aung, Z.2
Woon, W.L.3
-
22
-
-
0001287271
-
Regression shrinkage and selection via the lasso
-
Tibshirani, R.: Regression shrinkage and selection via the lasso. J. Roy. Stat. Soc.: Ser. (Methodol.) 58(1), 267-288 (1996)
-
(1996)
J. Roy. Stat. Soc.: Ser. (Methodol.)
, vol.58
, Issue.1
, pp. 267-288
-
-
Tibshirani, R.1
|