{"id":"https://openalex.org/W2370712656","doi":null,"title":"Grid Load Forecasting Based on Least Squares Support Vector Machine","display_name":"Grid Load Forecasting Based on Least Squares Support Vector Machine","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2370712656","mag":"2370712656"},"language":"en","primary_location":{"id":"mag:2370712656","doi":null,"is_oa":false,"landing_page_url":"http://en.cnki.com.cn/Article_en/CJFDTOTAL-WJFZ200706009.htm","pdf_url":null,"source":{"id":"https://openalex.org/S2764664041","display_name":"Computer Technology and Development","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4320800559","host_organization_name":"China Computer Federation","host_organization_lineage":["https://openalex.org/P4320800559"],"host_organization_lineage_names":["China Computer Federation"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Computer Technology and Development","raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5100410529","display_name":"Bo Liu","orcid":"https://orcid.org/0000-0002-0951-3115","observed_orcids":["https://orcid.org/0000-0002-0951-3115"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bo Liu","raw_affiliation_strings":["National Lab"],"raw_orcid":"https://orcid.org/0000-0002-0951-3115","affiliations":[{"raw_affiliation_string":"National Lab","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100410529"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.00019999999494757503,"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/T12451","display_name":"Smart Grid and Power Systems","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/least-squares-support-vector-machine","display_name":"least squares support vector machine","score":0.9269999861717224},{"id":"https://openalex.org/keywords/wavelet-decomposition","display_name":"wavelet decomposition","score":0.9380000233650208},{"id":"https://openalex.org/keywords/short-term-load-forecasting","display_name":"short-term load forecasting","score":0.9599999785423279},{"id":"https://openalex.org/keywords/signal-decomposition","display_name":"signal decomposition","score":0.5649999976158142},{"id":"https://openalex.org/keywords/forecast-combination","display_name":"forecast combination","score":0.8640000224113464},{"id":"https://openalex.org/keywords/memory-load","display_name":"memory load","score":0.6190000176429749}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8490599989891052},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7215703725814819},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6888088583946228},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.60432368516922},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5959271192550659},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4605698883533478},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4537329077720642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4109998345375061},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3905273675918579},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38599514961242676},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3356691598892212},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0752485990524292},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2370712656","doi":null,"is_oa":false,"landing_page_url":"http://en.cnki.com.cn/Article_en/CJFDTOTAL-WJFZ200706009.htm","pdf_url":null,"source":{"id":"https://openalex.org/S2764664041","display_name":"Computer Technology and Development","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4320800559","host_organization_name":"China Computer Federation","host_organization_lineage":["https://openalex.org/P4320800559"],"host_organization_lineage_names":["China Computer Federation"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Computer Technology and Development","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5378999710083008}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2363427715","https://openalex.org/W2149092993","https://openalex.org/W2382227689","https://openalex.org/W2376022218","https://openalex.org/W2376382136","https://openalex.org/W2375546215","https://openalex.org/W2545488370","https://openalex.org/W2361592937","https://openalex.org/W2108943569","https://openalex.org/W2078749264"],"abstract_inverted_index":{"An":[0],"algorithm":[1],"for":[2],"grid":[3,25],"load":[4,26,70],"forecasting":[5,49,61],"based":[6],"on":[7,48],"wavelet":[8,65],"analysis":[9],"and":[10,27],"least":[11],"squares":[12],"support":[13],"vector":[14],"machine,was":[15],"introduced.Begin":[16],"with":[17],"discussion":[18],"of":[19,21,24,32,41,50],"decomposition":[20],"serial":[22],"signal":[23],"then":[28],"get":[29,59],"the":[30],"forecasts":[31],"each":[33],"sub-signals":[34],"by":[35],"LS-SVM.The":[36],"third":[37],"step":[38],"is":[39],"combination":[40],"these":[42],"forecasts.This":[43],"method":[44],"was":[45],"successfully":[46],"achieved":[47],"memory":[51],"load.The":[52],"experiment":[53],"result":[54],"shows":[55],"that":[56],"it":[57],"can":[58],"better":[60],"accuracy":[62],"to":[63],"traditional":[64],"neural":[66],"network":[67],"in":[68],"short-term":[69],"forecasting.":[71]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2025-10-10T17:16:08.811792","created_date":"2016-06-24T00:00:00"}
