Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: A new approach.

MLA

Deo, Ravinesh C., et al. “Universally Deployable Extreme Learning Machines Integrated with Remotely Sensed MODIS Satellite Predictors over Australia to Forecast Global Solar Radiation: A New Approach.” Renewable & Sustainable Energy Reviews, vol. 104, Apr. 2019, pp. 235–61. EBSCOhost, https://doi.org/10.1016/j.rser.2019.01.009.

APA

Deo, R. C., Şahin, M., Adamowski, J. F., & Mi, J. (2019). Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: A new approach. Renewable & Sustainable Energy Reviews, 104, 235–261. https://doi.org/10.1016/j.rser.2019.01.009

Chicago

Deo, Ravinesh C., Mehmet Şahin, Jan F. Adamowski, and Jianchun Mi. 2019. “Universally Deployable Extreme Learning Machines Integrated with Remotely Sensed MODIS Satellite Predictors over Australia to Forecast Global Solar Radiation: A New Approach.” Renewable & Sustainable Energy Reviews 104 (April): 235–61. doi:10.1016/j.rser.2019.01.009.