{"id":"doi:10.1016/j.scitotenv.2019.01.431","kind":"article","title":"Meteorological drought forecasting based on a statistical model with machine learning techniques in Shaanxi province, China","authors":["Rong Zhang","Zhaoyue Chen","Li-Jun Xu","Chun‐Quan Ou"],"author_count":4,"year":2019,"published":"2019-02-10","venue":"The Science of The Total Environment","cited_by":210,"doi":"10.1016/j.scitotenv.2019.01.431","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.scitotenv.2019.01.431","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.scitotenv.2019.01.431","updated":null,"pmid":"30772564","pmcid":null,"openalex_id":"W2913267705","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":["Hydrology and Drought Analysis"],"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":[]}