{"id":"https://openalex.org/W7130401443","doi":"https://doi.org/10.1109/ifeea66847.2025.11388894","title":"Electricity Price Forecasting Based on Similarity-Based Date Selection and VMD-CNN-LSTM","display_name":"Electricity Price Forecasting Based on Similarity-Based Date Selection and VMD-CNN-LSTM","publication_year":2025,"publication_date":"2025-11-07","ids":{"openalex":"https://openalex.org/W7130401443","doi":"https://doi.org/10.1109/ifeea66847.2025.11388894"},"language":"en","primary_location":{"id":"doi:10.1109/ifeea66847.2025.11388894","doi":"https://doi.org/10.1109/ifeea66847.2025.11388894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ifeea66847.2025.11388894","pdf_url":null,"source":{"id":"https://openalex.org/S4363605240","display_name":"International Forum on Electrical Engineering and Automation (IFEEA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Forum on Electrical Engineering and Automation (IFEEA)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5152024461","display_name":"Yingying Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingying Chen","raw_affiliation_strings":["Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125360146","display_name":"Dong LI","orcid":"https://orcid.org/0009-0008-9605-4383","observed_orcids":["https://orcid.org/0009-0008-9605-4383"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Li","raw_affiliation_strings":["Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126348548","display_name":"Wenhao Peng","orcid":"https://orcid.org/0000-0002-8900-5312","observed_orcids":["https://orcid.org/0000-0002-8900-5312"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhao Peng","raw_affiliation_strings":["Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100750944","display_name":"Yongcan Zhu","orcid":"https://orcid.org/0000-0001-5277-3935","observed_orcids":["https://orcid.org/0000-0001-5277-3935"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongcan Zhu","raw_affiliation_strings":["Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Polytechnic University,School of Electronics and Information,Xi’an,China","institution_ids":["https://openalex.org/I27599042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27599042"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59462473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"429","last_page":"433"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9961000084877014,"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":0.9961000084877014,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.0032999999821186066,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/electricity-price-forecasting","display_name":"electricity price forecasting","score":0.9779999852180481},{"id":"https://openalex.org/keywords/short-term-forecasting","display_name":"short-term forecasting","score":0.9589999914169312},{"id":"https://openalex.org/keywords/similar-day-selection","display_name":"similar day selection","score":0.7879999876022339},{"id":"https://openalex.org/keywords/variational-mode-decomposition","display_name":"variational mode decomposition","score":0.8180000185966492},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.6060000061988831},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"K-means clustering","score":0.7429999709129333},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"dynamic time warping","score":0.9679999947547913},{"id":"https://openalex.org/keywords/nonstationarity","display_name":"non-stationarity","score":0.7519999742507935},{"id":"https://openalex.org/keywords/renewable-energy-output","display_name":"renewable energy output","score":0.9160000085830688},{"id":"https://openalex.org/keywords/electricity-generation","display_name":"electricity generation","score":0.6370000243186951}],"concepts":[{"id":"https://openalex.org/C2781104810","wikidata":"https://www.wikidata.org/wiki/Q23580049","display_name":"Electricity price forecasting","level":4,"score":0.8303999900817871},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.6654999852180481},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5047000050544739},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.5019000172615051},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C2983129042","wikidata":"https://www.wikidata.org/wiki/Q870344","display_name":"Electricity price","level":3,"score":0.4643999934196472},{"id":"https://openalex.org/C2779280359","wikidata":"https://www.wikidata.org/wiki/Q870344","display_name":"Electricity pricing","level":4,"score":0.4474000036716461},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.43320000171661377},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4081000089645386},{"id":"https://openalex.org/C423512","wikidata":"https://www.wikidata.org/wiki/Q383973","display_name":"Electricity generation","level":3,"score":0.40299999713897705},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.3783000111579895},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.36980000138282776},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34470000863075256},{"id":"https://openalex.org/C146733006","wikidata":"https://www.wikidata.org/wiki/Q676081","display_name":"Electricity market","level":3,"score":0.3431999981403351},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.30630001425743103},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2851000130176544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2825999855995178},{"id":"https://openalex.org/C159744936","wikidata":"https://www.wikidata.org/wiki/Q1126730","display_name":"Spearman's rank correlation coefficient","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.26429998874664307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ifeea66847.2025.11388894","doi":"https://doi.org/10.1109/ifeea66847.2025.11388894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ifeea66847.2025.11388894","pdf_url":null,"source":{"id":"https://openalex.org/S4363605240","display_name":"International Forum on Electrical Engineering and Automation (IFEEA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Forum on Electrical Engineering and Automation (IFEEA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9090999960899353},{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5351999998092651},{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.428600013256073}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2000982976","https://openalex.org/W2158442843","https://openalex.org/W2613278213","https://openalex.org/W2772433304","https://openalex.org/W2902930959","https://openalex.org/W3120283405","https://openalex.org/W3198084268"],"related_works":["https://openalex.org/W4405305912","https://openalex.org/W4401362643","https://openalex.org/W4405786832","https://openalex.org/W4414270917","https://openalex.org/W7220396256","https://openalex.org/W4309002792","https://openalex.org/W7117521459","https://openalex.org/W3186129726","https://openalex.org/W4409548512","https://openalex.org/W4392552198"],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,85,124],"challenges":[3],"of":[4],"strong":[5],"non-stationarity":[6],"and":[7,32,40,56,62,110,132],"high":[8],"prediction":[9,109,130],"difficulty":[10],"in":[11],"electricity":[12,22,51,86,119],"prices":[13],"under":[14],"multi-factor":[15],"coupling,":[16],"this":[17],"paper":[18],"proposes":[19],"a":[20,35,78,116],"short-term":[21],"price":[23,87,120],"forecasting":[24],"model":[25],"integrating":[26],"hybrid":[27],"feature":[28],"selection,":[29,31],"similar-day":[30],"VMD-CNN-LSTM.":[33],"First,":[34],"two-dimensional":[36],"analysis":[37],"using":[38],"Pearson":[39],"Spearman":[41],"correlation":[42],"coefficients":[43],"identifies":[44],"five":[45],"key":[46],"features":[47,101],"significantly":[48,128],"correlated":[49],"with":[50,69],"prices\u2014including":[52],"renewable":[53],"energy":[54],"output":[55],"total":[57],"power":[58],"generation\u2014to":[59],"reduce":[60,95],"dimensionality":[61],"eliminate":[63],"redundancy.":[64],"Next,":[65],"K-means":[66],"clustering":[67],"combined":[68],"Dynamic":[70],"Time":[71],"Warping":[72],"selects":[73],"similar":[74],"days":[75],"to":[76,94,137],"construct":[77],"high-quality":[79],"training":[80],"dataset.":[81],"Subsequently,":[82],"VMD":[83],"decomposed":[84],"sequence":[88],"into":[89],"11":[90],"stationary":[91],"eigenmode":[92],"functions":[93],"complexity.":[96],"Finally,":[97],"CNN":[98],"extracted":[99],"spatial":[100],"while":[102],"LSTM":[103],"uncovered":[104],"long-term":[105],"temporal":[106],"dependencies,":[107],"completing":[108],"result":[111],"reconstruction.":[112],"Experimental":[113],"results":[114],"on":[115],"northwest":[117],"China":[118],"dataset":[121],"demonstrate":[122],"that":[123],"proposed":[125],"method":[126],"achieves":[127],"lower":[129],"errors":[131],"more":[133],"stable":[134],"performance":[135],"compared":[136],"baseline":[138],"models,":[139],"validating":[140],"its":[141],"effectiveness.":[142]},"counts_by_year":[],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2026-02-19T00:00:00"}