{"id":"https://openalex.org/W4411383099","doi":"https://doi.org/10.32604/cmc.2025.063373","title":"Utility of Graph Neural Networks in Short-to Medium-Range Weather Forecasting","display_name":"Utility of Graph Neural Networks in Short-to Medium-Range Weather Forecasting","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411383099","doi":"https://doi.org/10.32604/cmc.2025.063373"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.063373","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063373","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.063373","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011353779","display_name":"Xiaoni Sun","orcid":"https://orcid.org/0009-0002-6640-7543"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xiaoni Sun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100679846","display_name":"Jiming Li","orcid":"https://orcid.org/0009-0000-2964-8650"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiming Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030958990","display_name":"Zhiqiang Zhao","orcid":"https://orcid.org/0000-0002-2475-7177"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002743894","display_name":"Guodong Jing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guodong Jing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057968680","display_name":"Baojun Chen","orcid":"https://orcid.org/0000-0003-4856-6196"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baojun Chen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028521210","display_name":"Jinrong Hu","orcid":"https://orcid.org/0000-0001-7732-8141"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinrong Hu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455714","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0001-5890-0448"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100675809","display_name":"Yong\u2010Wei Zhang","orcid":"https://orcid.org/0000-0001-7255-1678"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong Zhang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5011353779"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.6899,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.94987792,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"84","issue":"2","first_page":"2121","last_page":"2149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9135000109672546,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9135000109672546,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9049000144004822,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9027000069618225,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6076624989509583},{"id":"https://openalex.org/keywords/weather-forecasting","display_name":"Weather forecasting","score":0.5713334083557129},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5433725118637085},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5379735827445984},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.44426971673965454},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4117090106010437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39674222469329834},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19834300875663757},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11657923460006714},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11572656035423279}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6076624989509583},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.5713334083557129},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5433725118637085},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5379735827445984},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.44426971673965454},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4117090106010437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39674222469329834},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19834300875663757},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11657923460006714},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11572656035423279},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.063373","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063373","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.063373","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063373","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.8700000047683716,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1522265489","https://openalex.org/W1789155650","https://openalex.org/W2072319095","https://openalex.org/W2116341502","https://openalex.org/W2156936520","https://openalex.org/W2254553042","https://openalex.org/W2759136286","https://openalex.org/W2799899433","https://openalex.org/W2807252330","https://openalex.org/W2907492528","https://openalex.org/W2985331920","https://openalex.org/W3000120900","https://openalex.org/W3001630685","https://openalex.org/W3003709258","https://openalex.org/W3005160811","https://openalex.org/W3040144530","https://openalex.org/W3138340468","https://openalex.org/W3153880451","https://openalex.org/W3174292513","https://openalex.org/W3195489344","https://openalex.org/W3204702407","https://openalex.org/W4213064785","https://openalex.org/W4220977700","https://openalex.org/W4225586984","https://openalex.org/W4229042773","https://openalex.org/W4281484812","https://openalex.org/W4293447337","https://openalex.org/W4294068833","https://openalex.org/W4295950983","https://openalex.org/W4311081005","https://openalex.org/W4317211928","https://openalex.org/W4328008037","https://openalex.org/W4362579348","https://openalex.org/W4362579589","https://openalex.org/W4362627411","https://openalex.org/W4376643869","https://openalex.org/W4383056506","https://openalex.org/W4383197616","https://openalex.org/W4383218913","https://openalex.org/W4385855800","https://openalex.org/W4386034829","https://openalex.org/W4387763661","https://openalex.org/W4388654737","https://openalex.org/W4388728292","https://openalex.org/W4389069156","https://openalex.org/W4391881253","https://openalex.org/W4392081018","https://openalex.org/W4396817427","https://openalex.org/W4399594884","https://openalex.org/W4399794065","https://openalex.org/W4399915678","https://openalex.org/W4400880443","https://openalex.org/W4401724841","https://openalex.org/W4403589974","https://openalex.org/W4404482519","https://openalex.org/W4405023061","https://openalex.org/W4405031167","https://openalex.org/W4405179402","https://openalex.org/W4415500210"],"related_works":["https://openalex.org/W2789124470","https://openalex.org/W2958561312","https://openalex.org/W1480156024","https://openalex.org/W3092347950","https://openalex.org/W65938850","https://openalex.org/W275718980","https://openalex.org/W2361731950","https://openalex.org/W2618707070","https://openalex.org/W4223932376","https://openalex.org/W188660134"],"abstract_inverted_index":{"Weather":[0],"forecasting":[1,92,105],"is":[2],"crucial":[3],"for":[4,102],"agriculture,":[5],"transportation,":[6],"and":[7,94],"industry.":[8],"Deep":[9],"Learning":[10],"(DL)":[11],"has":[12],"greatly":[13],"improved":[14],"the":[15,58],"prediction":[16],"accuracy.":[17],"Among":[18],"them,":[19],"Graph":[20],"Neural":[21],"Networks":[22],"(GNNs)":[23],"excel":[24],"at":[25],"processing":[26],"weather":[27,65,104],"data":[28],"by":[29],"establishing":[30],"connections":[31],"between":[32],"regions.":[33],"This":[34],"allows":[35],"them":[36],"to":[37,90],"understand":[38],"complex":[39],"patterns":[40],"that":[41],"traditional":[42],"methods":[43,68],"might":[44],"miss.":[45],"As":[46],"a":[47],"result,":[48],"achieving":[49],"more":[50],"accurate":[51],"predictions":[52],"becomes":[53],"possible.":[54],"The":[55,67,78],"paper":[56,79],"reviews":[57],"role":[59],"of":[60],"GNNs":[61],"in":[62],"short-to":[63],"medium-range":[64],"forecasting.":[66],"are":[69],"classified":[70],"into":[71],"three":[72],"categories":[73],"based":[74],"on":[75],"dataset":[76],"differences.":[77],"also":[80],"further":[81],"identifies":[82],"five":[83],"promising":[84],"research":[85],"frontiers.":[86],"These":[87],"areas":[88],"aim":[89],"boost":[91],"precision":[93],"enhance":[95],"computational":[96],"efficiency.":[97],"They":[98],"offer":[99],"valuable":[100],"insights":[101],"future":[103],"systems.":[106]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-19T08:26:33.389920","created_date":"2025-10-10T00:00:00"}
