{"id":"https://openalex.org/W2725058992","doi":"https://doi.org/10.3390/en10070874","title":"Energy-Related CO2 Emissions Forecasting Using an Improved LSSVM Model Optimized by Whale Optimization Algorithm","display_name":"Energy-Related CO2 Emissions Forecasting Using an Improved LSSVM Model Optimized by Whale Optimization Algorithm","publication_year":2017,"publication_date":"2017-06-29","ids":{"openalex":"https://openalex.org/W2725058992","doi":"https://doi.org/10.3390/en10070874","mag":"2725058992"},"language":"en","primary_location":{"id":"doi:10.3390/en10070874","doi":"https://doi.org/10.3390/en10070874","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en10070874","pdf_url":"https://www.mdpi.com/1996-1073/10/7/874/pdf?version=1498732837","source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"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":"Energies","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1996-1073/10/7/874/pdf?version=1498732837","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101666224","display_name":"Haoran Zhao","orcid":"https://orcid.org/0000-0003-4480-2577","observed_orcids":["https://orcid.org/0000-0003-4480-2577"]},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Zhao","raw_affiliation_strings":["School of Economics and Management, North China Electric Power University, Beijing 102206, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100709736","display_name":"Sen Guo","orcid":"https://orcid.org/0000-0003-0866-3944","observed_orcids":["https://orcid.org/0000-0003-0866-3944","https://orcid.org/0000-0002-4368-3644"]},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sen Guo","raw_affiliation_strings":["School of Economics and Management, North China Electric Power University, Beijing 102206, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102964761","display_name":"Huiru Zhao","orcid":"https://orcid.org/0000-0002-3063-8377","observed_orcids":["https://orcid.org/0000-0002-3063-8377"]},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiru Zhao","raw_affiliation_strings":["School of Economics and Management, North China Electric Power University, Beijing 102206, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100709736"],"corresponding_institution_ids":["https://openalex.org/I153473198"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":11.0422,"has_fulltext":true,"cited_by_count":53,"citation_normalized_percentile":{"value":0.98152348,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"10","issue":"7","first_page":"874","last_page":"874"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10438","display_name":"Energy, Environment, Economic Growth","score":0.9570000171661377,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10438","display_name":"Energy, Environment, Economic Growth","score":0.9570000171661377,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.01269999984651804,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.003000000026077032,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/carbon-emissions-forecasting","display_name":"carbon emission prediction","score":0.9710000157356262},{"id":"https://openalex.org/keywords/least-squares-support-vector-machine","display_name":"least squares support vector machine","score":0.8930000066757202},{"id":"https://openalex.org/keywords/whale-optimization-algorithm","display_name":"whale optimization algorithm","score":0.9990000128746033},{"id":"https://openalex.org/keywords/parameter-optimization","display_name":"parameter optimization","score":0.7269999980926514},{"id":"https://openalex.org/keywords/energy-related-emissions","display_name":"energy-related emissions","score":0.5730000138282776},{"id":"https://openalex.org/keywords/driving-forces-of-emissions","display_name":"driving forces of emissions","score":0.765999972820282},{"id":"https://openalex.org/keywords/gross-domestic-product","display_name":"gross domestic product","score":0.8510000109672546},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"energy consumption","score":0.9990000128746033},{"id":"https://openalex.org/keywords/population","display_name":"population","score":0.968999981880188},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.4970000088214874},{"id":"https://openalex.org/keywords/nature-inspired-algorithms","display_name":"bio-inspired algorithms","score":0.6690000295639038},{"id":"https://openalex.org/keywords/fruit-fly-optimization-algorithm","display_name":"fruit fly optimization algorithm","score":0.8820000290870667}],"concepts":[{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5920704007148743},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.5319267511367798},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5218086242675781},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.5187525749206543},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4547227919101715},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.446682333946228},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34058523178100586},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3214213252067566},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20772439241409302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1932862401008606},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18126872181892395}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/en10070874","doi":"https://doi.org/10.3390/en10070874","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en10070874","pdf_url":"https://www.mdpi.com/1996-1073/10/7/874/pdf?version=1498732837","source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"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":"Energies","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:gam:jeners:v:10:y:2017:i:7:p:874-:d:103042","doi":null,"is_oa":false,"landing_page_url":"https://www.mdpi.com/1996-1073/10/7/874/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/en10070874","doi":"https://doi.org/10.3390/en10070874","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en10070874","pdf_url":"https://www.mdpi.com/1996-1073/10/7/874/pdf?version=1498732837","source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"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":"Energies","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":1.0},{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5690000057220459}],"study_designs":[],"awards":[{"id":"https://openalex.org/G3480047338","display_name":null,"funder_award_id":"2017MS060","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6937095626","display_name":null,"funder_award_id":"2016YFB0900501","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8799685953","display_name":"\u7535\u529b\u666e\u904d\u670d\u52a1\u793e\u4f1a\u798f\u5229\u6f0f\u635f\u53ca\u5176\u8865\u507f\u673a\u5236\u7814\u7a76","funder_award_id":"71373076","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2725058992.pdf","grobid_xml":"https://content.openalex.org/works/W2725058992.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1559526330","https://openalex.org/W1943902465","https://openalex.org/W1965014002","https://openalex.org/W1965684405","https://openalex.org/W1971663872","https://openalex.org/W1992114951","https://openalex.org/W1993183401","https://openalex.org/W1993923554","https://openalex.org/W1995779840","https://openalex.org/W1995789178","https://openalex.org/W2007470835","https://openalex.org/W2022912953","https://openalex.org/W2030760030","https://openalex.org/W2031118743","https://openalex.org/W2036461557","https://openalex.org/W2039480094","https://openalex.org/W2042816221","https://openalex.org/W2048159757","https://openalex.org/W2059172641","https://openalex.org/W2068206361","https://openalex.org/W2070902746","https://openalex.org/W2071151783","https://openalex.org/W2071551700","https://openalex.org/W2074222154","https://openalex.org/W2074590122","https://openalex.org/W2077967478","https://openalex.org/W2089235565","https://openalex.org/W2094565518","https://openalex.org/W2110674283","https://openalex.org/W2144641000","https://openalex.org/W2210975561","https://openalex.org/W2290883490","https://openalex.org/W2316286409","https://openalex.org/W2321327717"],"related_works":["https://openalex.org/W2795153861","https://openalex.org/W2791217703","https://openalex.org/W2965720486","https://openalex.org/W2975108999","https://openalex.org/W2814408658","https://openalex.org/W2983620935","https://openalex.org/W2990474957","https://openalex.org/W3090601702","https://openalex.org/W2784245535","https://openalex.org/W2285944352"],"abstract_inverted_index":{"Accurate":[0],"and":[1,19,109,162],"reliable":[2],"forecasting":[3,37,136],"on":[4],"energy-related":[5],"carbon":[6],"dioxide":[7],"(CO2)":[8],"emissions":[9,30,40,58,101,126,135,172,188],"is":[10,41,46,61,137,148],"of":[11,28,81,84,99,118,132,170,186],"great":[12],"significance":[13],"for":[14,38,203],"climate":[15],"policy":[16],"decision":[17],"making":[18],"energy":[20,107],"planning.":[21],"Due":[22],"to":[23,76,113,151,181],"the":[24,35,65,71,78,92,96,115,119,130,145,179,184,198,201],"complicated":[25],"nonlinear":[26],"relationships":[27],"CO2":[29,39,57,100,125,134,171,187],"with":[31],"its":[32],"driving":[33,97],"forces,":[34],"accurate":[36],"a":[42,55,192],"tedious":[43],"work,":[44],"which":[45,63],"an":[47,128],"important":[48],"issue":[49],"worth":[50],"studying.":[51],"In":[52],"this":[53],"study,":[54],"novel":[56],"prediction":[59],"method":[60],"proposed":[62,120,175],"employs":[64],"latest":[66],"nature-enlightened":[67,194],"optimization":[68,73,159,196],"method,":[69],"named":[70],"Whale":[72],"algorithm":[74],"(WOA),":[75],"search":[77],"optimized":[79],"values":[80],"two":[82],"parameters":[83],"LSSVM":[85],"(least":[86],"squares":[87],"support":[88],"vector":[89],"machine),":[90],"namely":[91,155],"WOA-LSSVM":[93,121,146,176],"model.":[94],"Meanwhile,":[95,190],"forces":[98],"including":[102],"GDP":[103],"(gross":[104],"domestic":[105],"product),":[106],"consumption":[108],"population":[110],"are":[111],"chosen":[112],"be":[114],"import":[116],"variables":[117],"method.":[122],"Taking":[123],"China\u2019s":[124],"as":[127,191],"instance,":[129],"effectiveness":[131],"WOA-LSSVM-based":[133],"verified.":[138],"The":[139,174],"comparative":[140],"analysis":[141],"results":[142],"indicate":[143],"that":[144],"model":[147,177],"significantly":[149],"superior":[150],"other":[152],"selected":[153],"models,":[154],"FOA":[156],"(fruit":[157],"fly":[158],"algorithm)-LSSVM,":[160],"LSSVM,":[161],"OLS":[163],"(ordinary":[164],"least":[165],"square)":[166],"models":[167],"in":[168],"terms":[169],"forecasting.":[173,189],"has":[178,200],"potential":[180],"effectively":[182],"improve":[183],"accuracy":[185],"new":[193],"heuristic":[195],"algorithm,":[197],"WOA":[199],"prospect":[202],"wide":[204],"application.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":7}],"updated_date":"2026-09-27T08:07:27.782135","created_date":"2017-07-14T00:00:00"}
