{"id":"https://openalex.org/W3135726705","doi":"https://doi.org/10.1109/access.2021.3064029","title":"Prediction of Dissolved Oxygen Content in Aquaculture Based on Clustering and Improved ELM","display_name":"Prediction of Dissolved Oxygen Content in Aquaculture Based on Clustering and Improved ELM","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3135726705","doi":"https://doi.org/10.1109/access.2021.3064029","mag":"3135726705"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3064029","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3064029","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09370107.pdf","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://ieeexplore.ieee.org/ielx7/6287639/9312710/09370107.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020608176","display_name":"Shouqi Cao","orcid":"https://orcid.org/0000-0003-2865-1449"},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouqi Cao","raw_affiliation_strings":["College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China","Shanghai Engineering Research Center of Marine Renewable Energy, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China","institution_ids":["https://openalex.org/I44675526"]},{"raw_affiliation_string":"Shanghai Engineering Research Center of Marine Renewable Energy, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102005945","display_name":"Lixin Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Zhou","raw_affiliation_strings":["College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China","Shanghai Engineering Research Center of Marine Renewable Energy, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9615-1721","affiliations":[{"raw_affiliation_string":"College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China","institution_ids":["https://openalex.org/I44675526"]},{"raw_affiliation_string":"Shanghai Engineering Research Center of Marine Renewable Energy, Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100459076","display_name":"Zheng Zhang","orcid":"https://orcid.org/0000-0001-8083-7481"},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Zhang","raw_affiliation_strings":["College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China","Shanghai Engineering Research Center of Marine Renewable Energy, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8083-7481","affiliations":[{"raw_affiliation_string":"College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China","institution_ids":["https://openalex.org/I44675526"]},{"raw_affiliation_string":"Shanghai Engineering Research Center of Marine Renewable Energy, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I44675526"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.1955,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.8657011,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"40372","last_page":"40387"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9993000030517578,"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":0.9993000030517578,"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/T12676","display_name":"Machine Learning and ELM","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9861999750137329,"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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6659176349639893},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6553657054901123},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.597222089767456},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5805680155754089},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.521441638469696},{"id":"https://openalex.org/keywords/collinearity","display_name":"Collinearity","score":0.5040037035942078},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.48705795407295227},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.42909711599349976},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42148810625076294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37201759219169617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2657691538333893},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.24392181634902954},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18638819456100464},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15172424912452698}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6659176349639893},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6553657054901123},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.597222089767456},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5805680155754089},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.521441638469696},{"id":"https://openalex.org/C106192678","wikidata":"https://www.wikidata.org/wiki/Q1419761","display_name":"Collinearity","level":2,"score":0.5040037035942078},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.48705795407295227},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.42909711599349976},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42148810625076294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37201759219169617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2657691538333893},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24392181634902954},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18638819456100464},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15172424912452698}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3064029","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3064029","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09370107.pdf","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:50f4d5bcd2ae41379904a266ac95bccc","is_oa":true,"landing_page_url":"https://doaj.org/article/50f4d5bcd2ae41379904a266ac95bccc","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 9, Pp 40372-40387 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3064029","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3064029","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09370107.pdf","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":[{"display_name":"Clean water and sanitation","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/6"}],"awards":[{"id":"https://openalex.org/G8042412221","display_name":null,"funder_award_id":"2019YFD090080","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3135726705.pdf","grobid_xml":"https://content.openalex.org/works/W3135726705.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W842171740","https://openalex.org/W1988115241","https://openalex.org/W1989788921","https://openalex.org/W1993488142","https://openalex.org/W1996436491","https://openalex.org/W1998462925","https://openalex.org/W2000360734","https://openalex.org/W2010770993","https://openalex.org/W2023767556","https://openalex.org/W2029748544","https://openalex.org/W2031667904","https://openalex.org/W2033179381","https://openalex.org/W2040940481","https://openalex.org/W2062861257","https://openalex.org/W2063773269","https://openalex.org/W2069976783","https://openalex.org/W2070986256","https://openalex.org/W2075153278","https://openalex.org/W2075436252","https://openalex.org/W2109364787","https://openalex.org/W2111072639","https://openalex.org/W2118667718","https://openalex.org/W2124178519","https://openalex.org/W2129066856","https://openalex.org/W2134754332","https://openalex.org/W2141695047","https://openalex.org/W2156387975","https://openalex.org/W2282064529","https://openalex.org/W2301776921","https://openalex.org/W2341969817","https://openalex.org/W2349029087","https://openalex.org/W2354139054","https://openalex.org/W2355360040","https://openalex.org/W2373248314","https://openalex.org/W2386845456","https://openalex.org/W2415839891","https://openalex.org/W2509818319","https://openalex.org/W2568681765","https://openalex.org/W2588220372","https://openalex.org/W2751451600","https://openalex.org/W2763160615","https://openalex.org/W2776533265","https://openalex.org/W2909334078","https://openalex.org/W2966070016","https://openalex.org/W2997770686","https://openalex.org/W3085707493","https://openalex.org/W3095469680","https://openalex.org/W3095559896","https://openalex.org/W3117701875","https://openalex.org/W4251769717","https://openalex.org/W6682889407","https://openalex.org/W6695420950","https://openalex.org/W6746889408","https://openalex.org/W6986548558"],"related_works":["https://openalex.org/W2159670039","https://openalex.org/W4226120311","https://openalex.org/W2058928070","https://openalex.org/W3016530894","https://openalex.org/W4233429336","https://openalex.org/W4396771927","https://openalex.org/W3196914014","https://openalex.org/W4256422528","https://openalex.org/W2937099569","https://openalex.org/W3005992387"],"abstract_inverted_index":{"In":[0,31,132],"the":[1,20,41,47,77,84,90,102,109,113,127,140,166,169],"aquaculture":[2],"industry,":[3],"dissolved":[4,16,44,196],"oxygen":[5,17,45],"is":[6,37,99,123],"an":[7,187],"important":[8],"water":[9],"quality":[10],"parameter":[11],"index.":[12],"The":[13,143],"prediction":[14,153,158],"of":[15,23,43,49,96,105,157,180],"can":[18,150,172],"reduce":[19],"operation":[21],"cost":[22],"aquatic":[24],"product":[25],"management":[26],"to":[27,39,75,88,107,112,125,138,194],"a":[28,34],"certain":[29],"extent.":[30],"this":[32],"paper,":[33],"hybrid":[35],"method":[36,122],"proposed":[38],"predict":[40],"change":[42,92],"from":[46],"perspective":[48],"time":[50,182],"series":[51],"in":[52],"aquaculture,":[53],"which":[54],"based":[55],"on":[56],"k-means":[57,73],"clustering":[58],"and":[59,94,155,177],"improved":[60,170],"Softplus":[61,98],"extreme":[62],"learning":[63],"machine":[64],"(SELM)":[65],"with":[66,160,165],"particle":[67],"swarm":[68],"optimization":[69],"(PSO).":[70],"We":[71],"use":[72],"algorithm":[74,137],"divide":[76],"dataset":[78],"into":[79],"several":[80],"clusters":[81],"by":[82],"calculating":[83],"similarity":[85],"among":[86,130],"variables,":[87],"find":[89],"periodic":[91],"rule":[93],"trend":[95],"variables.":[97,131],"employed":[100],"as":[101],"activation":[103,115],"function":[104],"ELM":[106],"make":[108],"model":[110,141,149,171,190],"closer":[111],"biological":[114],"model.":[116],"Meanwhile,":[117],"partial":[118],"least":[119],"square":[120],"(PLS)":[121],"utilized":[124],"solve":[126],"strong":[128],"collinearity":[129],"addition,":[133],"we":[134],"introduce":[135],"PSO":[136],"optimize":[139],"parameters.":[142],"experimental":[144],"results":[145],"show":[146],"that":[147],"our":[148],"achieve":[151],"better":[152],"performance":[154],"accuracy":[156],"compared":[159],"other":[161],"single":[162],"models.":[163],"Compared":[164],"counterpart":[167],"model,":[168],"tolerate":[173],"some":[174],"data":[175],"loss":[176],"uncertain":[178],"outliers":[179],"sensor":[181],"series.":[183],"Our":[184],"work":[185],"provides":[186],"accurate":[188],"predictive":[189],"framework":[191],"for":[192],"researchers":[193],"track":[195],"oxygen.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}
