Cote S, Tatnall A R L. A neural network-based method for tracking features from satellite sensor images[J]. Int J Remote Sens, 1995, 16 (18): 3695-3701.
[2]
Hammer A, Heinemann D, Hoyer C, et al. Solar energy assessment using remote sensing technologies[J]. Remote Sens Environ, 2003, 86(3): 423-432.
[3]
Kaifel A K, Jesemann P. An adaptive filtering algorithm for very short-range forecast of cloudiness applied to Meteosat data[R]. Proc. 9th Meteosat Users Meeting, Locarno, 1992.
[4]
Armstrong M A. Comparison of MM5 forecast shortwave radiation with data obtained from the atmospheric radiation measurement program[D]. Maryland: University of Maryland, 2000.
[5]
Lorenz E, Remund J, Muller S, et al. Benchmarking of different approaches to forecast solar irradiance[R]. 24th European Photovoltaic Solar Energy Conference, Hamburg, 2009: 1-10.
Lange M. On the uncertainty of wind power predictions-analysis of the forecast accuracy and statistical distribution of errors[J]. Journal of Solar Energy Engineering, 2005, 127(2): 177-184, doi: 10.1115/1.1862266.
[20]
Lange M. Analysis of the uncertainty of wind power predictions[D]. Oldenburg: University of Oldenburg, 浏览
