{"id":"https://openalex.org/W2932101913","doi":"https://doi.org/10.3390/s19071562","title":"Prediction of Marine Pycnocline Based on Kernel Support Vector Machine and Convex Optimization Technology","display_name":"Prediction of Marine Pycnocline Based on Kernel Support Vector Machine and Convex Optimization Technology","publication_year":2019,"publication_date":"2019-03-31","ids":{"openalex":"https://openalex.org/W2932101913","doi":"https://doi.org/10.3390/s19071562","mag":"2932101913","pmid":"https://pubmed.ncbi.nlm.nih.gov/30935145"},"language":"en","primary_location":{"id":"doi:10.3390/s19071562","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19071562","pdf_url":"https://www.mdpi.com/1424-8220/19/7/1562/pdf?version=1554349794","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/19/7/1562/pdf?version=1554349794","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066144350","display_name":"Jiachen Yang","orcid":"https://orcid.org/0000-0003-2558-552X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachen Yang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China"],"raw_orcid":"https://orcid.org/0000-0003-2558-552X","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383262","display_name":"Lin Liu","orcid":"https://orcid.org/0000-0001-7558-7289"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100689119","display_name":"Linfeng Zhang","orcid":"https://orcid.org/0000-0003-4773-2279"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linfeng Zhang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357027","display_name":"Gen Li","orcid":"https://orcid.org/0000-0002-5596-8567"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gen Li","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048258685","display_name":"Zhonghao Sun","orcid":"https://orcid.org/0000-0003-1073-8538"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhonghao Sun","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079301418","display_name":"Houbing Song","orcid":"https://orcid.org/0000-0003-2631-9223"},"institutions":[{"id":"https://openalex.org/I84475105","display_name":"Embry\u2013Riddle Aeronautical University","ror":"https://ror.org/010jskt71","country_code":"US","type":"education","lineage":["https://openalex.org/I84475105"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Houbing Song","raw_affiliation_strings":["Department of Electrical, Computer, Software and Systems Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA"],"raw_orcid":"https://orcid.org/0000-0003-2631-9223","affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, Software and Systems Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA","institution_ids":["https://openalex.org/I84475105"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100357027"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.4555,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67537429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"19","issue":"7","first_page":"1562","last_page":"1562"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9958000183105469,"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":0.9958000183105469,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9732999801635742,"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/T12676","display_name":"Machine Learning and ELM","score":0.9713000059127808,"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/pycnocline","display_name":"Pycnocline","score":0.9206111431121826},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6919981837272644},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6059035658836365},{"id":"https://openalex.org/keywords/argo","display_name":"Argo","score":0.6014623641967773},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5833041667938232},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.5613601803779602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5442852973937988},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.47775593400001526},{"id":"https://openalex.org/keywords/ocean-gyre","display_name":"Ocean gyre","score":0.4488169252872467},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4331575036048889},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.363373726606369},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.18357545137405396},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.09617036581039429},{"id":"https://openalex.org/keywords/oceanography","display_name":"Oceanography","score":0.09515842795372009}],"concepts":[{"id":"https://openalex.org/C128963330","wikidata":"https://www.wikidata.org/wiki/Q1478740","display_name":"Pycnocline","level":2,"score":0.9206111431121826},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6919981837272644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6059035658836365},{"id":"https://openalex.org/C51614570","wikidata":"https://www.wikidata.org/wiki/Q647931","display_name":"Argo","level":2,"score":0.6014623641967773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5833041667938232},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.5613601803779602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5442852973937988},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.47775593400001526},{"id":"https://openalex.org/C30380174","wikidata":"https://www.wikidata.org/wiki/Q1250263","display_name":"Ocean gyre","level":3,"score":0.4488169252872467},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4331575036048889},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.363373726606369},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.18357545137405396},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.09617036581039429},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.09515842795372009},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.0},{"id":"https://openalex.org/C14168384","wikidata":"https://www.wikidata.org/wiki/Q16305538","display_name":"Subtropics","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/s19071562","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19071562","pdf_url":"https://www.mdpi.com/1424-8220/19/7/1562/pdf?version=1554349794","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:30935145","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30935145","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:9fc5eda31c014c16b765a28db291725b","is_oa":true,"landing_page_url":"https://doaj.org/article/9fc5eda31c014c16b765a28db291725b","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":"Sensors, Vol 19, Iss 7, p 1562 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/19/7/1562/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s19071562","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:6479887","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6479887","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:works.bepress.com:houbing_song-1454","is_oa":false,"landing_page_url":"https://works.bepress.com/houbing_song/347","pdf_url":null,"source":{"id":"https://openalex.org/S4377196356","display_name":"Scholarly Commons (Embry\u2013Riddle Aeronautical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I84475105","host_organization_name":"Embry\u2013Riddle Aeronautical University","host_organization_lineage":["https://openalex.org/I84475105"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Houbing Song","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3390/s19071562","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19071562","pdf_url":"https://www.mdpi.com/1424-8220/19/7/1562/pdf?version=1554349794","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.800000011920929}],"awards":[{"id":"https://openalex.org/G5981443170","display_name":null,"funder_award_id":"No. 61871283","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8191841786","display_name":"\u57fa\u4e8e\u4e09\u7406\u6c47\u901a\u7684\u865a\u62df\u73b0\u5b9e\u4f53\u9a8c\u8d28\u91cf\u8bc4\u4ef7\u7814\u7a76","funder_award_id":"61871283","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/W2932101913.pdf","grobid_xml":"https://content.openalex.org/works/W2932101913.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W349182000","https://openalex.org/W1964940342","https://openalex.org/W1974812662","https://openalex.org/W1976073160","https://openalex.org/W2010365692","https://openalex.org/W2010415387","https://openalex.org/W2021714746","https://openalex.org/W2036043678","https://openalex.org/W2057463561","https://openalex.org/W2061973027","https://openalex.org/W2068106516","https://openalex.org/W2073786081","https://openalex.org/W2076167486","https://openalex.org/W2084678032","https://openalex.org/W2100235303","https://openalex.org/W2105952797","https://openalex.org/W2106819216","https://openalex.org/W2110929188","https://openalex.org/W2113564250","https://openalex.org/W2113584252","https://openalex.org/W2152418738","https://openalex.org/W2152593845","https://openalex.org/W2153268005","https://openalex.org/W2158001550","https://openalex.org/W2164684831","https://openalex.org/W2173259274","https://openalex.org/W2176519433","https://openalex.org/W2331519844","https://openalex.org/W2342230329","https://openalex.org/W2346227481","https://openalex.org/W2462101293","https://openalex.org/W2759189196","https://openalex.org/W2770641139","https://openalex.org/W2792277382","https://openalex.org/W2896242594","https://openalex.org/W3163925938"],"related_works":["https://openalex.org/W2588056802","https://openalex.org/W2913841190","https://openalex.org/W2294878717","https://openalex.org/W2944576356","https://openalex.org/W2324174505","https://openalex.org/W2295685401","https://openalex.org/W2801025603","https://openalex.org/W813038129","https://openalex.org/W2149994643","https://openalex.org/W4315491844"],"abstract_inverted_index":{"With":[0],"the":[1,32,34,45,65,83,88,94,102,114,124,140,152,167,173,179,183,188,201,205,209,225,232,241,246,257,261,265,268,274,278,286],"explosive":[2],"growth":[3],"of":[4,9,31,105,126,142,190,204,231,248,267],"ocean":[5,14,19,35,46,74],"data,":[6],"it":[7],"is":[8,38,99,133,157,163],"great":[10],"significance":[11],"to":[12,17,27,135,165,223,244],"use":[13],"observation":[15],"data":[16,21,37,48,51,76,97,207],"analyze":[18,245],"pycnocline":[20,90,106,154,168],"in":[22,57,121,169],"military":[23],"field.":[24],"However,":[25],"due":[26],"natural":[28],"factors,":[29],"most":[30],"time":[33],"hydrological":[36,47,75],"not":[39,238],"complete.":[40],"In":[41,60,172],"this":[42,61,122,176],"case,":[43],"predicting":[44],"by":[49,138,197,285],"partial":[50],"has":[52],"become":[53],"a":[54,72,213],"hot":[55],"spot":[56],"marine":[58],"science.":[59],"paper,":[62,123],"based":[63,86,290],"on":[64,87,150,277,291],"traditional":[66,89,258],"statistical":[67],"analysis":[68],"literature,":[69],"we":[70],"propose":[71],"machine-learning":[73],"processing":[77],"process":[78],"under":[79],"big":[80],"data.":[81],"At":[82,264],"same":[84],"time,":[85],"gradient":[91,210],"determination":[92],"method,":[93],"open":[95],"Argo":[96],"set":[98,156,192,196],"analyzed,":[100],"and":[101,129,145,159,186,193,212,229,260],"local":[103],"characteristics":[104],"are":[107,282],"verified":[108],"from":[109],"several":[110],"aspects":[111],"combined":[112],"with":[113,182,217,250],"current":[115],"research":[116],"about":[117],"pycnocline.":[118],"Most":[119],"importantly,":[120],"combination":[125],"kernel":[127],"function":[128],"support":[130],"vector":[131],"machine(SVM)":[132],"extended":[134],"nonlinear":[136],"learning":[137,144],"using":[139],"idea":[141],"machine":[143],"convex":[146],"optimization":[147],"technology.":[148],"Based":[149],"this,":[151],"known":[153],"training":[155,191],"trained,":[158],"an":[160],"accurate":[161],"model":[162],"obtained":[164],"predict":[166],"unknown":[170],"domains.":[171],"specific":[174],"steps,":[175],"paper":[177],"combines":[178],"classification":[180],"problem":[181],"regression":[184],"problem,":[185],"determines":[187],"proportion":[189],"test":[194],"formula":[195],"polynomial":[198],"regression.":[199],"Subsequently,":[200],"feature":[202,287],"scaling":[203],"input":[206],"accelerated":[208],"convergence,":[211],"grid":[214],"search":[215],"algorithm":[216,289],"variable":[218,251],"step":[219,252],"size":[220],"was":[221],"proposed":[222],"determine":[224],"super":[226],"parameter":[227],"c":[228],"gamma":[230],"SVM":[233,259],"model.":[234],"The":[235],"prediction":[236],"results":[237],"only":[239],"used":[240],"confusion":[242],"matrix":[243],"accuracy":[247],"GridSearch-SVM":[249],"size,":[253],"but":[254],"also":[255],"compared":[256],"similar":[262],"algorithm.":[263],"end":[266],"experiment,":[269],"two":[270],"features":[271],"which":[272],"have":[273],"greatest":[275],"influence":[276],"Marine":[279],"density":[280],"thermocline":[281],"found":[283],"out":[284],"ranking":[288],"learning.":[292]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}
