{"id":"https://openalex.org/W7161989389","doi":"https://doi.org/10.1016/j.asoc.2026.115537","title":"Enhancing daily runoff forecasting with a dual-domain deep learning model","display_name":"Enhancing daily runoff forecasting with a dual-domain deep learning model","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7161989389","doi":"https://doi.org/10.1016/j.asoc.2026.115537"},"language":"en","primary_location":{"id":"doi:10.1016/j.asoc.2026.115537","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.asoc.2026.115537","pdf_url":null,"source":{"id":"https://openalex.org/S140556538","display_name":"Applied Soft Computing","issn_l":"1568-4946","issn":["1568-4946","1872-9681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Soft Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074094490","display_name":"Wenchuan Wang","orcid":"https://orcid.org/0000-0003-1367-5886"},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wen-chuan Wang","raw_affiliation_strings":["College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China"],"raw_orcid":"https://orcid.org/0000-0003-1367-5886","affiliations":[{"raw_affiliation_string":"College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109121642","display_name":"C. SHI","orcid":null},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can-can Shi","raw_affiliation_strings":["College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052433644","display_name":"Hong-fei Zang","orcid":null},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong-fei Zang","raw_affiliation_strings":["College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136695420","display_name":"Dong-mei Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong-mei Xu","raw_affiliation_strings":["College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, PR China","institution_ids":["https://openalex.org/I198645480"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5074094490"],"corresponding_institution_ids":["https://openalex.org/I198645480"],"apc_list":{"value":3350,"currency":"USD","value_usd":3350},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.58753335,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"201","issue":null,"first_page":"115537","last_page":"115537"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.5831000208854675,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.5831000208854675,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.20409999787807465,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.03620000183582306,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7497000098228455},{"id":"https://openalex.org/keywords/surface-runoff","display_name":"Surface runoff","score":0.4542999863624573},{"id":"https://openalex.org/keywords/deep-water","display_name":"Deep water","score":0.37599998712539673},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32429999113082886}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7497000098228455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5719000101089478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5694000124931335},{"id":"https://openalex.org/C50477045","wikidata":"https://www.wikidata.org/wiki/Q1444790","display_name":"Surface runoff","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C2988134249","wikidata":"https://www.wikidata.org/wiki/Q22932371","display_name":"Deep water","level":2,"score":0.37599998712539673},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36410000920295715},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.32829999923706055},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.29179999232292175},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.asoc.2026.115537","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.asoc.2026.115537","pdf_url":null,"source":{"id":"https://openalex.org/S140556538","display_name":"Applied Soft Computing","issn_l":"1568-4946","issn":["1568-4946","1872-9681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Soft Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.4020651578903198}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1531333757","https://openalex.org/W1985582992","https://openalex.org/W2055412520","https://openalex.org/W2117014758","https://openalex.org/W2753621571","https://openalex.org/W2908904086","https://openalex.org/W2911964244","https://openalex.org/W2954257334","https://openalex.org/W2970950689","https://openalex.org/W2971993235","https://openalex.org/W3006192077","https://openalex.org/W3026191193","https://openalex.org/W3095724529","https://openalex.org/W3117825698","https://openalex.org/W3132169264","https://openalex.org/W3174658340","https://openalex.org/W4205767161","https://openalex.org/W4294724153","https://openalex.org/W4309614510","https://openalex.org/W4313830014","https://openalex.org/W4322772399","https://openalex.org/W4360951932","https://openalex.org/W4385336257","https://openalex.org/W4387643951","https://openalex.org/W4388686886","https://openalex.org/W4390727419","https://openalex.org/W4393160869","https://openalex.org/W4393935449","https://openalex.org/W4395003185","https://openalex.org/W4401051949","https://openalex.org/W4401346287","https://openalex.org/W4402469109","https://openalex.org/W4402715273","https://openalex.org/W4403629600","https://openalex.org/W4405861075","https://openalex.org/W4406106932","https://openalex.org/W4406589145","https://openalex.org/W4412528630","https://openalex.org/W4413276958"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2026-05-22T00:00:00"}
