{"id":"https://openalex.org/W3109663333","doi":"https://doi.org/10.1109/access.2020.3042180","title":"An Enhanced Naive Bayes Model for Dissolved Oxygen Forecasting in Shellfish Aquaculture","display_name":"An Enhanced Naive Bayes Model for Dissolved Oxygen Forecasting in Shellfish Aquaculture","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3109663333","doi":"https://doi.org/10.1109/access.2020.3042180","mag":"3109663333"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3042180","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042180","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09279333.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/ielx7/6287639/6514899/09279333.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103111599","display_name":"Dashe Li","orcid":"https://orcid.org/0000-0003-3792-8964"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dashe Li","raw_affiliation_strings":["Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041407824","display_name":"Jiajun Sun","orcid":"https://orcid.org/0000-0001-5529-6660"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Sun","raw_affiliation_strings":["Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103184995","display_name":"Huanhai Yang","orcid":"https://orcid.org/0000-0003-2061-6980"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanhai Yang","raw_affiliation_strings":["Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100425322","display_name":"Xueying Wang","orcid":"https://orcid.org/0000-0001-7078-2165"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueying Wang","raw_affiliation_strings":["Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103111599"],"corresponding_institution_ids":["https://openalex.org/I83776822"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.8035,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.72509535,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"217917","last_page":"217927"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9860000014305115,"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":0.9860000014305115,"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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9804999828338623,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9801999926567078,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.709686279296875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4646764397621155},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.45719611644744873},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.45305293798446655},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.43224406242370605},{"id":"https://openalex.org/keywords/shellfish","display_name":"Shellfish","score":0.42815423011779785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4121040403842926},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4113863408565521},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3186994194984436},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.22994786500930786},{"id":"https://openalex.org/keywords/fishery","display_name":"Fishery","score":0.20604652166366577},{"id":"https://openalex.org/keywords/fish-actinopterygii","display_name":"Fish <Actinopterygii>","score":0.16465795040130615},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.11372306942939758},{"id":"https://openalex.org/keywords/aquatic-animal","display_name":"Aquatic animal","score":0.11075982451438904},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.0787191092967987}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.709686279296875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4646764397621155},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.45719611644744873},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.45305293798446655},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.43224406242370605},{"id":"https://openalex.org/C2781028344","wikidata":"https://www.wikidata.org/wiki/Q6501235","display_name":"Shellfish","level":4,"score":0.42815423011779785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4121040403842926},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4113863408565521},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3186994194984436},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.22994786500930786},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.20604652166366577},{"id":"https://openalex.org/C2909208804","wikidata":"https://www.wikidata.org/wiki/Q127282","display_name":"Fish <Actinopterygii>","level":2,"score":0.16465795040130615},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.11372306942939758},{"id":"https://openalex.org/C158278297","wikidata":"https://www.wikidata.org/wiki/Q1756633","display_name":"Aquatic animal","level":3,"score":0.11075982451438904},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0787191092967987},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3042180","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042180","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09279333.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:f9177beecdf240c0a28dd784460f291f","is_oa":true,"landing_page_url":"https://doaj.org/article/f9177beecdf240c0a28dd784460f291f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 8, Pp 217917-217927 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3042180","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042180","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09279333.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":[{"id":"https://metadata.un.org/sdg/14","score":0.7300000190734863,"display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3162017210","display_name":null,"funder_award_id":"201803","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3602114385","display_name":null,"funder_award_id":"61602277","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4878265459","display_name":null,"funder_award_id":"61772319","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5149596334","display_name":null,"funder_award_id":"2018031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8391063077","display_name":null,"funder_award_id":"61472227","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3109663333.pdf","grobid_xml":"https://content.openalex.org/works/W3109663333.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W313647156","https://openalex.org/W1971169262","https://openalex.org/W1985497040","https://openalex.org/W1988523865","https://openalex.org/W2000842688","https://openalex.org/W2004514718","https://openalex.org/W2016210396","https://openalex.org/W2016311539","https://openalex.org/W2020771758","https://openalex.org/W2039240409","https://openalex.org/W2040503026","https://openalex.org/W2040549706","https://openalex.org/W2058972628","https://openalex.org/W2065818856","https://openalex.org/W2074300736","https://openalex.org/W2101234009","https://openalex.org/W2133111499","https://openalex.org/W2151417892","https://openalex.org/W2156639545","https://openalex.org/W2158778494","https://openalex.org/W2162979574","https://openalex.org/W2167958905","https://openalex.org/W2223481328","https://openalex.org/W2234845577","https://openalex.org/W2286787740","https://openalex.org/W2296609147","https://openalex.org/W2329208669","https://openalex.org/W2335953718","https://openalex.org/W2466409464","https://openalex.org/W2470451742","https://openalex.org/W2479390720","https://openalex.org/W2550576290","https://openalex.org/W2565788240","https://openalex.org/W2581378775","https://openalex.org/W2609812488","https://openalex.org/W2617137052","https://openalex.org/W2738574859","https://openalex.org/W2741793919","https://openalex.org/W2760273722","https://openalex.org/W2762645278","https://openalex.org/W2769470793","https://openalex.org/W2775280337","https://openalex.org/W2785762403","https://openalex.org/W2792874300","https://openalex.org/W2797545377","https://openalex.org/W2801998166","https://openalex.org/W2809211493","https://openalex.org/W2911893501","https://openalex.org/W2950104637","https://openalex.org/W2952014779","https://openalex.org/W3022716520","https://openalex.org/W3099215482","https://openalex.org/W3104282666","https://openalex.org/W4248220371","https://openalex.org/W4253826867","https://openalex.org/W4255582690","https://openalex.org/W6675354045","https://openalex.org/W6747812261"],"related_works":["https://openalex.org/W2557895307","https://openalex.org/W2086787697","https://openalex.org/W230091440","https://openalex.org/W2094907188","https://openalex.org/W1958884951","https://openalex.org/W1483547336","https://openalex.org/W2367032735","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W2417174640"],"abstract_inverted_index":{"It":[0],"is":[1,34,52,93,130,180],"difficult":[2],"to":[3,36,55,99,132,168,182,192,256],"predict":[4,38,183],"dissolved":[5,17,39,61,88,156,185,202,230],"oxygen":[6,18,40,62,89,157,186,203,231],"values":[7,149,216],"because":[8],"they":[9],"are":[10],"disordered":[11],"and":[12,30,107,138,142,154,211,213,249,266],"nonlinear.":[13],"Accurate":[14],"prediction":[15,84,278],"of":[16,59,103,116,144,173,205,217,262],"in":[19,26,43,72,118,196],"shellfish":[20,28,207],"aquaculture":[21],"plays":[22],"an":[23,46],"important":[24],"role":[25],"improving":[27],"production,":[29],"a":[31,206,276],"reliable":[32],"model":[33,51],"needed":[35],"accurately":[37,160],"values.":[41,232],"Therefore,":[42,86],"this":[44],"paper,":[45],"enhanced":[47],"naive":[48],"Bayes":[49],"(NB)":[50],"proposed.":[53],"Due":[54],"the":[56,83,87,96,101,109,114,119,122,134,140,145,155,164,169,178,184,214,218,228,239,257,263,272],"excessive":[57],"number":[58,102,115],"different":[60],"values,":[63],"their":[64,225],"direct":[65],"use":[66],"as":[67,95,152],"input":[68,97],"samples":[69,117],"will":[70],"result":[71],"overly":[73],"few":[74],"training":[75,104,110,120,146,175],"set":[76,105],"categories":[77,106],"for":[78],"each":[79],"value,":[80],"which":[81],"reduces":[82],"accuracy.":[85,111,279],"differential":[90,135],"series":[91],"dataset":[92,137],"used":[94,131,181],"data":[98,158,187,204],"reduce":[100],"improve":[108],"To":[112],"increase":[113],"set,":[121],"sliding":[123],"window":[124],"concept":[125],"from":[126,188],"network":[127],"communication":[128],"protocols":[129],"partition":[133],"sequence":[136],"generate":[139],"features":[141],"labels":[143,165],"set.":[147],"The":[148,201,233,260],"were":[150,159,209,221],"predicted":[151,161,229],"categories,":[153],"by":[162,223],"selecting":[163],"that":[166,271],"correspond":[167],"posterior":[170],"probability":[171],"maxima":[172],"all":[174],"samples.":[176],"Finally,":[177],"algorithm":[179,235,274],"February":[189],"18,":[190],"2016,":[191],"January":[193],"31,":[194],"2020,":[195],"Yantai,":[197],"Shandong":[198],"Province,":[199],"China.":[200],"farm":[208],"trained":[210],"predicted,":[212],"best":[215],"feature":[219],"lengths":[220],"optimized":[222],"analyzing":[224],"effects":[226],"on":[227],"proposed":[234,273],"has":[236,275],"significantly":[237],"improved":[238],"mean":[240,245,250],"absolute":[241,251],"error":[242,247,253],"(MAE),":[243],"root":[244],"square":[246],"(RMSE),":[248],"percentage":[252],"(MAPE)":[254],"compared":[255],"advanced":[258],"algorithms.":[259],"results":[261],"Diebold-Mariano":[264],"test":[265],"10-fold":[267],"cross-validation":[268],"also":[269],"show":[270],"higher":[277]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}