{"id":"https://openalex.org/W2126764809","doi":"https://doi.org/10.1109/cifer.2009.4937504","title":"Energy forward price prediction with a hybrid adaptive model","display_name":"Energy forward price prediction with a hybrid adaptive model","publication_year":2009,"publication_date":"2009-03-01","ids":{"openalex":"https://openalex.org/W2126764809","doi":"https://doi.org/10.1109/cifer.2009.4937504","mag":"2126764809"},"language":"en","primary_location":{"id":"doi:10.1109/cifer.2009.4937504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer.2009.4937504","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Symposium on Computational Intelligence for Financial Engineering","raw_type":"proceedings-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/A5102016580","display_name":"Hang T. Nguyen","orcid":"https://orcid.org/0009-0006-4772-9909"},"institutions":[{"id":"https://openalex.org/I169199633","display_name":"Aston University","ror":"https://ror.org/05j0ve876","country_code":"GB","type":"education","lineage":["https://openalex.org/I169199633"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Hang T. Nguyen","raw_affiliation_strings":["Neural Computing Research Group, School of Engineering and Applied Science, Aston University, UK","Neural Computing Research Group, School of Engineering and Applied Science, Aston University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Neural Computing Research Group, School of Engineering and Applied Science, Aston University, UK","institution_ids":["https://openalex.org/I169199633"]},{"raw_affiliation_string":"Neural Computing Research Group, School of Engineering and Applied Science, Aston University, United Kingdom","institution_ids":["https://openalex.org/I169199633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086695297","display_name":"Ian T. Nabney","orcid":"https://orcid.org/0000-0003-1513-993X"},"institutions":[{"id":"https://openalex.org/I169199633","display_name":"Aston University","ror":"https://ror.org/05j0ve876","country_code":"GB","type":"education","lineage":["https://openalex.org/I169199633"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ian T. Nabney","raw_affiliation_strings":["Neural Computing Research Group, School of Engineering and Applied Science, Aston University, UK","Neural Computing Research Group, School of Engineering and Applied Science, Aston University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Neural Computing Research Group, School of Engineering and Applied Science, Aston University, UK","institution_ids":["https://openalex.org/I169199633"]},{"raw_affiliation_string":"Neural Computing Research Group, School of Engineering and Applied Science, Aston University, United Kingdom","institution_ids":["https://openalex.org/I169199633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102016580"],"corresponding_institution_ids":["https://openalex.org/I169199633"],"apc_list":null,"apc_paid":null,"fwci":0.6096,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73071663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"66","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.9921000003814697,"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":0.9901000261306763,"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/autoregressive-conditional-heteroskedasticity","display_name":"Autoregressive conditional heteroskedasticity","score":0.8213706016540527},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6957778930664062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5734742879867554},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5696572065353394},{"id":"https://openalex.org/keywords/electricity-price","display_name":"Electricity price","score":0.5628371238708496},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5504976511001587},{"id":"https://openalex.org/keywords/electricity-market","display_name":"Electricity market","score":0.48752591013908386},{"id":"https://openalex.org/keywords/electricity-price-forecasting","display_name":"Electricity price forecasting","score":0.4845644533634186},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.4310840666294098},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4242817759513855},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4152473211288452},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.2893032729625702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17998963594436646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16695427894592285},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1465197503566742},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1357218623161316},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.12983179092407227},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11620044708251953}],"concepts":[{"id":"https://openalex.org/C23922673","wikidata":"https://www.wikidata.org/wiki/Q180752","display_name":"Autoregressive conditional heteroskedasticity","level":3,"score":0.8213706016540527},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6957778930664062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5734742879867554},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5696572065353394},{"id":"https://openalex.org/C2983129042","wikidata":"https://www.wikidata.org/wiki/Q870344","display_name":"Electricity price","level":3,"score":0.5628371238708496},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5504976511001587},{"id":"https://openalex.org/C146733006","wikidata":"https://www.wikidata.org/wiki/Q676081","display_name":"Electricity market","level":3,"score":0.48752591013908386},{"id":"https://openalex.org/C2781104810","wikidata":"https://www.wikidata.org/wiki/Q23580049","display_name":"Electricity price forecasting","level":4,"score":0.4845644533634186},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.4310840666294098},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4242817759513855},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4152473211288452},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2893032729625702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17998963594436646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16695427894592285},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1465197503566742},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1357218623161316},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.12983179092407227},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11620044708251953},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cifer.2009.4937504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer.2009.4937504","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Symposium on Computational Intelligence for Financial Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:publications.aston.ac.uk:7965","is_oa":false,"landing_page_url":"https://publications.aston.ac.uk/view/author/d1763711db0822a33b28dc4ec669187e.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306400483","display_name":"Aston Publications Explorer (Aston University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169199633","host_organization_name":"Aston University","host_organization_lineage":["https://openalex.org/I169199633"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"NonPeerReviewed"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.426.7291","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.426.7291","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://eprints.aston.ac.uk/7965/1/CIFEr2009.pdf","raw_type":"text"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/a5bee711-5799-453f-b758-825f598f9158","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/a5bee711-5799-453f-b758-825f598f9158","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Nguyen, H T & Nabney, I T 2009, Energy forward price prediction with a hybrid adaptive model. in IEEE Symposium on Computational Intelligence for Financial Engineering, 2009. CIFEr '09. IEEE Computer Society, United States, pp. 66-71. https://doi.org/10.1109/CIFER.2009.4937504","raw_type":"bookPart"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.7099999785423279,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1595322697","https://openalex.org/W1626341607","https://openalex.org/W1877390215","https://openalex.org/W1999996900","https://openalex.org/W2089442811","https://openalex.org/W2096249306","https://openalex.org/W2098927251","https://openalex.org/W2101272964","https://openalex.org/W2105934661","https://openalex.org/W2126484602","https://openalex.org/W2126709108","https://openalex.org/W2126831543","https://openalex.org/W2128404709","https://openalex.org/W2150722745","https://openalex.org/W2151310832","https://openalex.org/W2153136237","https://openalex.org/W2155482907","https://openalex.org/W2171916840","https://openalex.org/W2541275555","https://openalex.org/W4285719527","https://openalex.org/W6729295125"],"related_works":["https://openalex.org/W2347295811","https://openalex.org/W2369447767","https://openalex.org/W2378867766","https://openalex.org/W2162537764","https://openalex.org/W2034312879","https://openalex.org/W2883617008","https://openalex.org/W4389989272","https://openalex.org/W2780445776","https://openalex.org/W2099234808","https://openalex.org/W2239264439"],"abstract_inverted_index":{"This":[0,13,60],"paper":[1],"presents":[2],"a":[3,16,21,43],"forecasting":[4,81,98],"technique":[5,14,61],"for":[6],"forward":[7],"electricity/gas":[8,103],"prices,":[9],"one":[10],"day":[11],"ahead.":[12],"combines":[15],"Kalman":[17],"filter":[18],"(KF)":[19],"and":[20,102],"generalised":[22],"autoregressive":[23],"conditional":[24],"heteroschedasticity":[25],"(GARCH)":[26],"model":[27,35,53],"(often":[28],"used":[29,37],"in":[30],"financial":[31],"forecasting).":[32],"The":[33,46,76,91],"GARCH":[34,52],"is":[36,58,62,83],"to":[38,64,72,97],"compute":[39],"next":[40],"value":[41],"of":[42,50],"time":[44],"series.":[45],"KF":[47],"updates":[48],"parameters":[49],"the":[51,55,68,80],"when":[54],"new":[56],"observation":[57],"available.":[59],"applied":[63,96],"real":[65],"data":[66],"from":[67],"UK":[69],"energy":[70],"markets":[71],"evaluate":[73],"its":[74],"performance.":[75],"results":[77],"show":[78],"that":[79],"accuracy":[82],"improved":[84],"significantly":[85],"by":[86],"using":[87],"this":[88],"hybrid":[89],"model.":[90],"methodology":[92],"can":[93],"be":[94],"also":[95],"market":[99],"clearing":[100],"prices":[101],"loads.":[104]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
