{"id":"https://openalex.org/W2990570263","doi":"https://doi.org/10.1177/0142331219885273","title":"Kernel principal component analysis-based least squares support vector machine optimized by improved grey wolf optimization algorithm and application in dynamic liquid level forecasting of beam pump","display_name":"Kernel principal component analysis-based least squares support vector machine optimized by improved grey wolf optimization algorithm and application in dynamic liquid level forecasting of beam pump","publication_year":2019,"publication_date":"2019-11-18","ids":{"openalex":"https://openalex.org/W2990570263","doi":"https://doi.org/10.1177/0142331219885273","mag":"2990570263"},"language":"en","primary_location":{"id":"doi:10.1177/0142331219885273","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0142331219885273","pdf_url":null,"source":{"id":"https://openalex.org/S24148485","display_name":"Transactions of the Institute of Measurement and Control","issn_l":"0142-3312","issn":["0142-3312","1477-0369"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Institute of Measurement and Control","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069779326","display_name":"Zhongda Tian","orcid":"https://orcid.org/0000-0003-0379-4048"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tian Zhongda","raw_affiliation_strings":["College of Information Science and Engineering, Shenyang University of Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Shenyang University of Technology, China","institution_ids":["https://openalex.org/I157507598"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5069779326"],"corresponding_institution_ids":["https://openalex.org/I157507598"],"apc_list":null,"apc_paid":null,"fwci":3.4232,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.91866699,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"42","issue":"6","first_page":"1135","last_page":"1150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9804999828338623,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.599023163318634},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5331693291664124},{"id":"https://openalex.org/keywords/least-squares-support-vector-machine","display_name":"Least squares support vector machine","score":0.5205622315406799},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4775839149951935},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.45848414301872253},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44117850065231323},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4120247960090637},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35522404313087463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28996512293815613},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23322460055351257}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.599023163318634},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5331693291664124},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.5205622315406799},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4775839149951935},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.45848414301872253},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44117850065231323},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4120247960090637},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35522404313087463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28996512293815613},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23322460055351257},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/0142331219885273","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0142331219885273","pdf_url":null,"source":{"id":"https://openalex.org/S24148485","display_name":"Transactions of the Institute of Measurement and Control","issn_l":"0142-3312","issn":["0142-3312","1477-0369"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Institute of Measurement and Control","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W47232657","https://openalex.org/W588468042","https://openalex.org/W1596717185","https://openalex.org/W1986490585","https://openalex.org/W1986543815","https://openalex.org/W2025248735","https://openalex.org/W2057814586","https://openalex.org/W2060258062","https://openalex.org/W2061438946","https://openalex.org/W2074993972","https://openalex.org/W2087754676","https://openalex.org/W2094565518","https://openalex.org/W2151872005","https://openalex.org/W2289618405","https://openalex.org/W2327277999","https://openalex.org/W2344100260","https://openalex.org/W2346457778","https://openalex.org/W2406369699","https://openalex.org/W2411718431","https://openalex.org/W2467163588","https://openalex.org/W2507944451","https://openalex.org/W2523236392","https://openalex.org/W2529650139","https://openalex.org/W2530660889","https://openalex.org/W2572535209","https://openalex.org/W2581679970","https://openalex.org/W2588187389","https://openalex.org/W2590737959","https://openalex.org/W2594054146","https://openalex.org/W2603605794","https://openalex.org/W2742365644","https://openalex.org/W2767079012","https://openalex.org/W2769354266","https://openalex.org/W2782749104","https://openalex.org/W2788859094","https://openalex.org/W2791354555","https://openalex.org/W2792244305","https://openalex.org/W2792396409","https://openalex.org/W2802397810","https://openalex.org/W2802713807","https://openalex.org/W2807998741","https://openalex.org/W4230835027","https://openalex.org/W4247878399"],"related_works":["https://openalex.org/W2122277321","https://openalex.org/W2382231800","https://openalex.org/W2018632273","https://openalex.org/W2538830880","https://openalex.org/W2350302603","https://openalex.org/W2134202645","https://openalex.org/W2394871888","https://openalex.org/W2769345709","https://openalex.org/W2372354349","https://openalex.org/W2371052470"],"abstract_inverted_index":{"Considering":[0],"the":[1,6,45,58,71,81,89,101,112,115,128,141,150,157,172,182,205,214],"blind":[2],"parameters":[3,55,73,94],"selection":[4,56],"and":[5,84,122,130,143,149],"high":[7],"dimension":[8],"of":[9,49,57,74,88,95,118,137,146,160,166,184],"input":[10,116,133,138,153],"data":[11,197],"in":[12],"least":[13],"squares":[14],"support":[15],"vector":[16],"machine":[17],"(LSSVM)":[18],"modeling":[19,147],"process,":[20,148],"a":[21],"kernel":[22],"principal":[23],"component":[24],"analysis":[25],"(KPCA)-based":[26],"LSSVM":[27,50,96,119],"forecasting":[28,43,47,177,207],"method":[29,178,208],"optimized":[30,106],"by":[31,54,107],"improved":[32,61,77,108],"grey":[33],"wolf":[34],"optimization":[35,82,86,102],"(GWO)":[36],"algorithm":[37,63,79,125],"is":[38,51,67,105,169,179,198],"proposed.":[39],"As":[40],"an":[41],"excellent":[42],"model,":[44],"regression":[46],"performance":[48,66,212],"greatly":[52],"affected":[53],"model.":[59],"An":[60],"GWO":[62,78,91,109],"with":[64],"better":[65,210],"proposed":[68,176,206],"to":[69,155,181],"determine":[70],"optimal":[72],"LSSVM.":[75,161],"This":[76],"improves":[80],"precision":[83],"global":[85],"ability":[87],"standard":[90],"algorithm.":[92,110],"The":[93,135,162,175,188,200],"model":[97],"are":[98,120],"taken":[99],"as":[100,171],"object":[103],"that":[104,204],"At":[111],"same":[113],"time,":[114],"variables":[117,139],"correlated":[121],"redundant.":[123],"KPCA":[124],"can":[126],"eliminate":[127],"correlation":[129],"redundancy":[131],"between":[132,152],"variables.":[134],"reduction":[136],"reduces":[140],"complexity":[142],"training":[144],"time":[145],"coupling":[151],"variables,":[154],"improve":[156],"prediction":[158,183],"accuracy":[159],"dynamic":[163,185,194,215],"liquid":[164,186,195,216],"level":[165,196],"beam":[167],"pump":[168],"chosen":[170],"research":[173],"object.":[174],"applied":[180],"level.":[187,217],"simulation":[189,201],"comparison":[190],"on":[191],"actual":[192],"collected":[193],"performed.":[199],"results":[202],"show":[203],"has":[209],"predictive":[211],"for":[213]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}