{"id":"https://openalex.org/W4404914600","doi":"https://doi.org/10.1109/access.2024.3509744","title":"Water Quality Prediction Method Based on Reinforcement Learning Graph Neural Network","display_name":"Water Quality Prediction Method Based on Reinforcement Learning Graph Neural Network","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4404914600","doi":"https://doi.org/10.1109/access.2024.3509744"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3509744","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3509744","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3509744","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112316339","display_name":"Mingming Yan","orcid":"https://orcid.org/0009-0007-6325-7507"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingming Yan","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, Hubei, China","Wuhan University of Science and technology, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0009-0007-6325-7507","affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I43922553"]},{"raw_affiliation_string":"Wuhan University of Science and technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100407681","display_name":"Zhe Wang","orcid":"https://orcid.org/0000-0003-4102-1353"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Wang","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, Hubei, China","Wuhan University of Science and technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I43922553"]},{"raw_affiliation_string":"Wuhan University of Science and technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I43922553"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I43922553"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4621,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.80397907,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"184421","last_page":"184430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.5181999802589417,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing 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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.5181999802589417,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing 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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.4982999861240387,"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"}},{"id":"https://openalex.org/T14225","display_name":"Advanced Sensor and Control Systems","score":0.49380001425743103,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.779370903968811},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7159545421600342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5773189663887024},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5648607015609741},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4971306622028351},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4699806272983551},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16594049334526062}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.779370903968811},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7159545421600342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5773189663887024},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5648607015609741},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4971306622028351},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4699806272983551},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16594049334526062}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3509744","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3509744","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3e19ee486d4747329d26244a4b06e294","is_oa":true,"landing_page_url":"https://doaj.org/article/3e19ee486d4747329d26244a4b06e294","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 184421-184430 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3509744","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3509744","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","score":0.75,"id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W305081305","https://openalex.org/W1720514416","https://openalex.org/W2070986256","https://openalex.org/W2116341502","https://openalex.org/W2546155378","https://openalex.org/W2581896076","https://openalex.org/W2888788502","https://openalex.org/W2890096158","https://openalex.org/W2948456504","https://openalex.org/W2963076818","https://openalex.org/W2964015378","https://openalex.org/W2971388538","https://openalex.org/W2973106087","https://openalex.org/W3006101764","https://openalex.org/W3008408706","https://openalex.org/W3034671389","https://openalex.org/W3080150692","https://openalex.org/W3113873473","https://openalex.org/W3153387564","https://openalex.org/W3160154289","https://openalex.org/W3181978631","https://openalex.org/W3197183970","https://openalex.org/W3198362553","https://openalex.org/W3209731954","https://openalex.org/W4214706788","https://openalex.org/W4214905413","https://openalex.org/W4220666015","https://openalex.org/W4225374983","https://openalex.org/W4295329718","https://openalex.org/W4313594236","https://openalex.org/W4324360024","https://openalex.org/W4386959351","https://openalex.org/W4387643882","https://openalex.org/W4389942701","https://openalex.org/W6628877408","https://openalex.org/W6738964360","https://openalex.org/W6748370023","https://openalex.org/W6757677476"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"The":[0,85],"importance":[1],"of":[2,80,91],"water":[3,28,71,81,99,134],"quality":[4,29,72,82,100,135],"prediction":[5,101],"for":[6],"management":[7],"and":[8,31,37,65,110,133],"pollution":[9],"control":[10],"has":[11],"gained":[12],"significant":[13,120],"recognition":[14],"in":[15],"recent":[16],"years.":[17],"However,":[18],"existing":[19],"methods":[20],"face":[21],"two":[22],"main":[23],"challenges:":[24],"the":[25,32,78,89,143],"interaction":[26],"between":[27],"variables":[30],"environment":[33],"is":[34,42,102],"often":[35],"overlooked,":[36],"even":[38],"when":[39],"considered,":[40],"it":[41],"not":[43],"effectively":[44],"utilized.":[45],"To":[46],"address":[47],"these":[48],"issues,":[49],"we":[50,122],"propose":[51],"a":[52,92,105,119],"reinforcement":[53,63,75],"learning":[54,76],"graph":[55,67,95],"neural":[56],"network-based":[57],"approach.":[58],"Our":[59],"method,":[60],"an":[61,111],"adjacency":[62,79],"learning,":[64],"multi-channel":[66],"convolution":[68,96],"autoencoder,":[69],"predicts":[70],"by":[73],"performing":[74],"on":[77,118],"indicator":[83,136],"images.":[84],"obtained":[86],"adjacencies":[87],"inform":[88],"design":[90],"triple-channel":[93],"adjacency-attention":[94],"network.":[97],"Ultimately,":[98],"achieved":[103],"through":[104],"deep":[106],"autoencoder":[107],"clustering":[108],"method":[109,117],"auto-regression":[112],"model.":[113],"We":[114],"evaluate":[115],"this":[116],"dataset":[121],"collected,":[123],"achieving":[124],"strong":[125],"experimental":[126],"results.":[127],"Additionally,":[128],"ablation":[129],"experiments,":[130],"robustness":[131],"analysis,":[132],"complexity":[137],"experiments":[138],"are":[139],"conducted":[140],"to":[141],"validate":[142],"method\u2019s":[144],"effectiveness.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
