{"id":"https://openalex.org/W4411405859","doi":"https://doi.org/10.1109/access.2025.3580741","title":"A Hybrid Deep Learning Model for Water Quality Prediction","display_name":"A Hybrid Deep Learning Model for Water Quality Prediction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411405859","doi":"https://doi.org/10.1109/access.2025.3580741"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3580741","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3580741","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2025.3580741","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103190807","display_name":"Qiliang Zhu","orcid":"https://orcid.org/0000-0002-7977-9672"},"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":"Qiliang Zhu","raw_affiliation_strings":["College of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7977-9672","affiliations":[{"raw_affiliation_string":"College of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou, China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101220174","display_name":"Xueting Yu","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":"Xueting Yu","raw_affiliation_strings":["College of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-5725-7594","affiliations":[{"raw_affiliation_string":"College of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou, China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101836736","display_name":"Liang Zhao","orcid":"https://orcid.org/0000-0003-1556-969X"},"institutions":[{"id":"https://openalex.org/I4210132981","display_name":"Ningxia Water Conservancy","ror":"https://ror.org/02p2qrw13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132981"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Zhao","raw_affiliation_strings":["Water Conservancy and Irrigation District Engineering Construction Administration of Xixiayuan Water Conservancy Project, Zhengzhou, China","Water Conservancy and Irrigation District Engineering Construction Administration of Xixia yuan Water Conservancy Project, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Water Conservancy and Irrigation District Engineering Construction Administration of Xixiayuan Water Conservancy Project, Zhengzhou, China","institution_ids":["https://openalex.org/I4210132981"]},{"raw_affiliation_string":"Water Conservancy and Irrigation District Engineering Construction Administration of Xixia yuan Water Conservancy Project, Zhengzhou, China","institution_ids":["https://openalex.org/I4210132981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113828601","display_name":"Linjun Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132981","display_name":"Ningxia Water Conservancy","ror":"https://ror.org/02p2qrw13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132981"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linjun Xu","raw_affiliation_strings":["Water Conservancy and Irrigation District Engineering Construction Administration of Xixiayuan Water Conservancy Project, Zhengzhou, China","Water Conservancy and Irrigation District Engineering Construction Administration of Xixia yuan Water Conservancy Project, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Water Conservancy and Irrigation District Engineering Construction Administration of Xixiayuan Water Conservancy Project, Zhengzhou, China","institution_ids":["https://openalex.org/I4210132981"]},{"raw_affiliation_string":"Water Conservancy and Irrigation District Engineering Construction Administration of Xixia yuan Water Conservancy Project, Zhengzhou, China","institution_ids":["https://openalex.org/I4210132981"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.6218,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.96268723,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"13","issue":null,"first_page":"106406","last_page":"106415"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9793999791145325,"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"}},"topics":[{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9793999791145325,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9352999925613403,"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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9089999794960022,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7207503914833069},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5195872783660889},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5073258280754089},{"id":"https://openalex.org/keywords/water-quality","display_name":"Water quality","score":0.47247597575187683},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46452319622039795},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4466797411441803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7207503914833069},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5195872783660889},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5073258280754089},{"id":"https://openalex.org/C2780797713","wikidata":"https://www.wikidata.org/wiki/Q625376","display_name":"Water quality","level":2,"score":0.47247597575187683},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46452319622039795},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4466797411441803},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3580741","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3580741","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b1bcfbb541aa4c81bf3a6d6ef6dcec83","is_oa":true,"landing_page_url":"https://doaj.org/article/b1bcfbb541aa4c81bf3a6d6ef6dcec83","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 13, Pp 106406-106415 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3580741","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3580741","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"awards":[{"id":"https://openalex.org/G8701542639","display_name":"\u79fb\u52a8\u4e92\u8054\u73af\u5883\u4e0b\u51c6\u786e\u4e0e\u516c\u5e73\u517c\u987e\u7684\u670d\u52a1\u63a8\u8350\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61571066","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1660213354","https://openalex.org/W2125056386","https://openalex.org/W2625282162","https://openalex.org/W2888342334","https://openalex.org/W2930669685","https://openalex.org/W2936399818","https://openalex.org/W2948456504","https://openalex.org/W2950683703","https://openalex.org/W2980159178","https://openalex.org/W3005619874","https://openalex.org/W3027880148","https://openalex.org/W3110015110","https://openalex.org/W3166135633","https://openalex.org/W3166967148","https://openalex.org/W3214554842","https://openalex.org/W4200475582","https://openalex.org/W4206989389","https://openalex.org/W4281998028","https://openalex.org/W4283275666","https://openalex.org/W4284958113","https://openalex.org/W4285262293","https://openalex.org/W4293553219","https://openalex.org/W4387165236","https://openalex.org/W4391906391","https://openalex.org/W4403826722","https://openalex.org/W4404851038","https://openalex.org/W4408158728"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W4387369504","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Water":[0],"quality":[1,51,103,141,166],"prediction":[2,23],"is":[3],"crucial":[4],"for":[5],"water":[6,18,50,102,140,165],"environment":[7],"management,":[8],"playing":[9],"a":[10,28,33,87,106,159],"key":[11,123],"role":[12],"in":[13,65,100,150],"preventing":[14],"pollution":[15],"and":[16,62,148,156,161],"ensuring":[17],"resource":[19],"safety.":[20],"To":[21],"improve":[22],"accuracy,":[24],"this":[25],"paper":[26],"proposes":[27],"CEEMDAN-CNN-LSTM":[29],"model":[30,131,144],"enhanced":[31],"by":[32],"self-attention":[34,107],"mechanism.":[35],"First,":[36],"the":[37,49,66,77,81,94,101,119,129,151],"Complete":[38],"Ensemble":[39],"Empirical":[40],"Mode":[41,57],"Decomposition":[42],"with":[43],"Adaptive":[44],"Noise":[45],"(CEEMDAN)":[46],"algorithm":[47],"decomposes":[48],"time":[52,116],"series":[53],"into":[54],"multiple":[55,139],"Intrinsic":[56],"Functions":[58],"(IMFs),":[59],"reducing":[60],"noise":[61,149],"addressing":[63],"nonlinearities":[64],"data.":[67,104],"Next,":[68],"Convolutional":[69],"Neural":[70],"Networks":[71],"(CNN)":[72],"extract":[73],"spatial":[74,83],"features":[75,113],"from":[76],"decomposed":[78],"IMFs,":[79],"improving":[80,118],"model\u2019s":[82,120],"learning":[84],"capability.":[85],"Then,":[86],"Long":[88],"Short-Term":[89],"Memory":[90],"(LSTM)":[91],"network":[92],"models":[93],"temporal":[95],"features,":[96],"capturing":[97],"long-term":[98],"dependencies":[99],"Finally,":[105],"mechanism":[108],"assigns":[109],"varying":[110],"importance":[111],"to":[112,164],"at":[114],"different":[115],"steps,":[117],"focus":[121],"on":[122],"information.":[124],"Experimental":[125],"results":[126],"demonstrate":[127],"that":[128],"proposed":[130],"outperforms":[132],"traditional":[133],"methods,":[134],"achieving":[135],"high":[136],"accuracy":[137],"across":[138],"indicators.":[142],"This":[143],"effectively":[145],"addresses":[146],"non-stationarity":[147],"data,":[152],"demonstrating":[153],"strong":[154],"generalization":[155],"robustness,":[157],"providing":[158],"novel":[160],"efficient":[162],"approach":[163],"prediction.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}
