Optimized feed-forward neural networks to address CO2-equivalent emissions data gaps – Application to emissions prediction for unit processes of fuel life cycle inventories for Canadian provinces

Autor:	Sayyed Ahmad Khadem, Farid Bensebaa, Nathan Pelletier
Rok vydání:	2022
Předmět:	Renewable Energy Sustainability and the Environment Strategy and Management Building and Construction Industrial and Manufacturing Engineering General Environmental Science
Zdroj:	Journal of Cleaner Production. 332:130053
ISSN:	0959-6526
DOI:	10.1016/j.jclepro.2021.130053
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2c7d60e23452fd16baa3ce38433ea2fc https://doi.org/10.1016/j.jclepro.2021.130053 Zobrazit plný text záznamu Full Text from ScienceDirect