@article{(Open Science Index):https://publications.waset.org/pdf/10005381,
	  title     = {Using Gaussian Process in Wind Power Forecasting},
	  author    = {Hacene Benkhoula and  Mohamed Badreddine Benabdella and  Hamid Bouzeboudja and  Abderrahmane Asraoui},
	  country	= {},
	  institution	= {},
	  abstract     = {The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {10},
	  number    = {1},
	  year      = {2016},
	  pages     = {172 - 175},
	  ee        = {https://publications.waset.org/pdf/10005381},
	  url   	= {https://publications.waset.org/vol/109},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 109, 2016},
	}