{"id":"https://openalex.org/W3128698796","doi":"https://doi.org/10.1109/icmla51294.2020.00197","title":"Technical Indicators and Prediction for Energy Market Forecasting","display_name":"Technical Indicators and Prediction for Energy Market Forecasting","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3128698796","doi":"https://doi.org/10.1109/icmla51294.2020.00197","mag":"3128698796"},"language":"en","primary_location":{"id":"doi:10.1109/icmla51294.2020.00197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla51294.2020.00197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pure.ulster.ac.uk/ws/files/89066564/ICMLA2020_Acceptance_Paper_391.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059047583","display_name":"Catherine McHugh","orcid":"https://orcid.org/0000-0003-2948-9172"},"institutions":[{"id":"https://openalex.org/I138801177","display_name":"University of Ulster","ror":"https://ror.org/01yp9g959","country_code":"GB","type":"education","lineage":["https://openalex.org/I138801177"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Catherine McHugh","raw_affiliation_strings":["Intelligent Systems Research Centre, Ulster University, Northern Ireland, UK"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Research Centre, Ulster University, Northern Ireland, UK","institution_ids":["https://openalex.org/I138801177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070227862","display_name":"Sonya Coleman","orcid":"https://orcid.org/0000-0002-4676-7640"},"institutions":[{"id":"https://openalex.org/I138801177","display_name":"University of Ulster","ror":"https://ror.org/01yp9g959","country_code":"GB","type":"education","lineage":["https://openalex.org/I138801177"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sonya Coleman","raw_affiliation_strings":["Intelligent Systems Research Centre, Ulster University, Northern Ireland, UK"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Research Centre, Ulster University, Northern Ireland, UK","institution_ids":["https://openalex.org/I138801177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015138346","display_name":"Dermot Kerr","orcid":"https://orcid.org/0000-0002-5077-0658"},"institutions":[{"id":"https://openalex.org/I138801177","display_name":"University of Ulster","ror":"https://ror.org/01yp9g959","country_code":"GB","type":"education","lineage":["https://openalex.org/I138801177"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dermot Kerr","raw_affiliation_strings":["Intelligent Systems Research Centre, Ulster University, Northern Ireland, UK"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Research Centre, Ulster University, Northern Ireland, UK","institution_ids":["https://openalex.org/I138801177"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059047583"],"corresponding_institution_ids":["https://openalex.org/I138801177"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.16046048,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1254","last_page":"1259"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9944999814033508,"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/gradient-boosting","display_name":"Gradient boosting","score":0.6995896100997925},{"id":"https://openalex.org/keywords/technical-analysis","display_name":"Technical analysis","score":0.6653043627738953},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.6010256409645081},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5691575407981873},{"id":"https://openalex.org/keywords/electricity-market","display_name":"Electricity market","score":0.5686693787574768},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5572517514228821},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5392445921897888},{"id":"https://openalex.org/keywords/economic-indicator","display_name":"Economic indicator","score":0.5298497676849365},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.47350579500198364},{"id":"https://openalex.org/keywords/electricity-price-forecasting","display_name":"Electricity price forecasting","score":0.4596500098705292},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.317789226770401},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.2001962959766388},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.1443522572517395},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0956621766090393}],"concepts":[{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6995896100997925},{"id":"https://openalex.org/C117245426","wikidata":"https://www.wikidata.org/wiki/Q235038","display_name":"Technical analysis","level":2,"score":0.6653043627738953},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.6010256409645081},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5691575407981873},{"id":"https://openalex.org/C146733006","wikidata":"https://www.wikidata.org/wiki/Q676081","display_name":"Electricity market","level":3,"score":0.5686693787574768},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5572517514228821},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5392445921897888},{"id":"https://openalex.org/C202353208","wikidata":"https://www.wikidata.org/wiki/Q1167393","display_name":"Economic indicator","level":2,"score":0.5298497676849365},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.47350579500198364},{"id":"https://openalex.org/C2781104810","wikidata":"https://www.wikidata.org/wiki/Q23580049","display_name":"Electricity price forecasting","level":4,"score":0.4596500098705292},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.317789226770401},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2001962959766388},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.1443522572517395},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0956621766090393},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icmla51294.2020.00197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla51294.2020.00197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire/fcbf090b-6075-462b-8f41-09c08d0c70e4","is_oa":true,"landing_page_url":"https://pure.ulster.ac.uk/en/publications/fcbf090b-6075-462b-8f41-09c08d0c70e4","pdf_url":"https://pure.ulster.ac.uk/ws/files/89066564/ICMLA2020_Acceptance_Paper_391.pdf","source":{"id":"https://openalex.org/S4306402454","display_name":"Ulster University Research Portal (Ulster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138801177","host_organization_name":"University of Ulster","host_organization_lineage":["https://openalex.org/I138801177"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"McHugh, C, Coleman, S & Kerr, D 2020, 'Technical Indicators and Prediction for Energy Market Forecasting', Paper presented at 2020 19th IEEE International Conference on Machine Learning and Applications, 14/12/20 - 17/12/20 pp. 1241-1246.","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire/fcbf090b-6075-462b-8f41-09c08d0c70e4","is_oa":true,"landing_page_url":"https://pure.ulster.ac.uk/en/publications/fcbf090b-6075-462b-8f41-09c08d0c70e4","pdf_url":"https://pure.ulster.ac.uk/ws/files/89066564/ICMLA2020_Acceptance_Paper_391.pdf","source":{"id":"https://openalex.org/S4306402454","display_name":"Ulster University Research Portal (Ulster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138801177","host_organization_name":"University of Ulster","host_organization_lineage":["https://openalex.org/I138801177"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"McHugh, C, Coleman, S & Kerr, D 2020, 'Technical Indicators and Prediction for Energy Market Forecasting', Paper presented at 2020 19th IEEE International Conference on Machine Learning and Applications, 14/12/20 - 17/12/20 pp. 1241-1246.","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.5899999737739563,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3128698796.pdf","grobid_xml":"https://content.openalex.org/works/W3128698796.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1987860980","https://openalex.org/W1989182416","https://openalex.org/W1990497493","https://openalex.org/W2009772556","https://openalex.org/W2021664313","https://openalex.org/W2031939255","https://openalex.org/W2252909801","https://openalex.org/W2347175495","https://openalex.org/W2529091517","https://openalex.org/W2560125060","https://openalex.org/W2572554044","https://openalex.org/W2765895279","https://openalex.org/W2911814932","https://openalex.org/W2998160221","https://openalex.org/W3002226745","https://openalex.org/W3192434902","https://openalex.org/W4300511110","https://openalex.org/W6704825425"],"related_works":["https://openalex.org/W4246904700","https://openalex.org/W3036633074","https://openalex.org/W4388726391","https://openalex.org/W1588585209","https://openalex.org/W4388451786","https://openalex.org/W4313289168","https://openalex.org/W4388451310","https://openalex.org/W3211970770","https://openalex.org/W2913098687","https://openalex.org/W1565182317"],"abstract_inverted_index":{"Machine":[0],"learning":[1,101],"usage":[2],"for":[3,11,50,68],"forecasting":[4],"is":[5,17],"popular":[6],"in":[7,77],"financial":[8,42],"trading,":[9],"particularly":[10],"stock":[12],"price":[13,82,134],"prediction":[14],"and":[15,58,110],"this":[16],"often":[18],"combined":[19],"with":[20,114],"technical":[21,47,66,118,124,141,160],"indicators":[22,27,48,67,142],"to":[23,41,137],"extract":[24],"key":[25],"predictive":[26],"from":[28],"large":[29],"time":[30],"series":[31],"trading":[32,36,43,60],"datasets.":[33],"Energy":[34],"market":[35,76],"data":[37,83,135],"have":[38,63],"similar":[39],"characteristics":[40],"data,":[44],"therefore":[45],"deriving":[46],"specifically":[49],"electricity":[51,81,151],"prices":[52,57,152],"will":[53],"help":[54],"predict":[55],"future":[56],"reduce":[59],"costs.":[61],"We":[62,148],"derived":[64],"eight":[65],"the":[69,85,115,123,130,158],"Integrated":[70],"Single":[71],"Electricity":[72],"Market":[73],"(ISEM)":[74],"energy":[75],"Ireland":[78],"using":[79,99,140,157],"hourly":[80],"over":[84],"period":[86],"February":[87],"2019":[88],"until":[89],"November":[90],"2019.":[91],"Technical":[92],"indicator":[93,125],"based":[94],"models":[95,126],"were":[96,127],"obtained":[97],"by":[98],"machine":[100],"regression":[102],"algorithms":[103],"(Extreme":[104],"Gradient":[105,111],"[XG]":[106],"Boost,":[107],"Random":[108],"Forest,":[109],"Boosting)":[112],"trained":[113],"proposed":[116,159],"novel":[117],"indicators.":[119,161],"The":[120],"results":[121],"of":[122],"compared":[128],"against":[129],"baseline":[131],"model":[132,146],"(raw":[133],"only)":[136],"see":[138],"if":[139],"as":[143],"inputs":[144],"improves":[145],"performance.":[147],"conclude":[149],"that":[150],"can":[153],"be":[154],"accurately":[155],"predicted":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}