Comprehensive evaluation of wind speed distribution models: A case study for North Dakota sites
By Junyi Zhou, Ergin Erdem, Gong Li, Jing Shi. 2010
174 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/bc55012fd210a411b5ff147e3d06e2a77ec2fd6f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Luai M. Al-Hadhrami
- Shafiqur Rehman
- Taha B. M. J. Ouarda
- Christian Charron
- Mihalakakou Giouli
- H. S. Bagiorgas
In Environmental Engineering
- Luai M. Al-Hadhrami
- Shafiqur Rehman
- Taha B. M. J. Ouarda
- Christian Charron
- Mihalakakou Giouli
- H. S. Bagiorgas
Citations in the corpus
- Weibull Parameters Estimation Using Four Different Methods and Most Energy-Carrying Wind Speed Analysis (2011, background): “…density function is the most appropriate distribution function for wind speed data (Hennessey 1977; Justus et al. 1978; Bardsley 1980; Rehman et al., 1994; Garcia et al. 1998; Li and Li 2005; Bagiorgas et al. 2007; Gokcek et al. 2007; Ucar and Balo 2009; Qu and Shi 2010; Zhou et al. 2010).”
- On the mixture of wind speed distribution in a Nordic region (2018, background): “…three-parameter beta (B), Pearson type III (P3), log-Pearson type III (LP3), Burr (BR), Erlang 112 (ER), Johnson SB, kappa (KAP) and Wakeby (WA) (Carta et al., 2009; Zhou et al., 2010; Lo 113 Brano et al., 2011; Morgan et al., 2011; Masseran et al., 2012; Soukissian, 2013; Jung et al., 114 2017).”