Cite
A data-driven framework for designing a renewable energy community based on the integration of machine learning model with life cycle assessment and life cycle cost parameters.
MLA
Elomari, Youssef, et al. “A Data-Driven Framework for Designing a Renewable Energy Community Based on the Integration of Machine Learning Model with Life Cycle Assessment and Life Cycle Cost Parameters.” Applied Energy, vol. 358, Mar. 2024, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.apenergy.2024.122619.
APA
Elomari, Y., Mateu, C., Marín-Genescà, M., & Boer, D. (2024). A data-driven framework for designing a renewable energy community based on the integration of machine learning model with life cycle assessment and life cycle cost parameters. Applied Energy, 358, N.PAG. https://doi.org/10.1016/j.apenergy.2024.122619
Chicago
Elomari, Youssef, Carles Mateu, M. Marín-Genescà, and Dieter Boer. 2024. “A Data-Driven Framework for Designing a Renewable Energy Community Based on the Integration of Machine Learning Model with Life Cycle Assessment and Life Cycle Cost Parameters.” Applied Energy 358 (March): N.PAG. doi:10.1016/j.apenergy.2024.122619.