{"id":"doi:10.1016/j.renene.2020.04.042","kind":"article","title":"Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons","authors":["Zhihong Pang","Fuxin Niu","Zheng D. O’Neill"],"author_count":3,"year":2020,"published":"2020-04-13","venue":"Renewable Energy","cited_by":341,"doi":"10.1016/j.renene.2020.04.042","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.renene.2020.04.042","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.renene.2020.04.042","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W3016726239","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Solar Radiation and Photovoltaics"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"ai-weather-climate","name":"AI Weather & Climate Modeling","domain_slug":"energy"}],"cited_in_dossiers":[]}