{"id":"https://openalex.org/W7224550102","doi":"https://doi.org/10.55401/vj84sp67","title":"Machine Learning Framework for Short-term Photovoltaic PowerForecasting with Feature Selection and Power Range Error Analysis","display_name":"Machine Learning Framework for Short-term Photovoltaic PowerForecasting with Feature Selection and Power Range Error Analysis","publication_year":2026,"publication_date":"2026-10-29","ids":{"openalex":"https://openalex.org/W7224550102","doi":"https://doi.org/10.55401/vj84sp67"},"language":"en","primary_location":{"id":"doi:10.55401/vj84sp67","doi":"https://doi.org/10.55401/vj84sp67","is_oa":true,"landing_page_url":"https://doi.org/10.55401/vj84sp67","pdf_url":"https://jstdata.ntt.edu.vn/index.php/jst/article/download/1119/941","source":{"id":"https://openalex.org/S4220651663","display_name":"Journal of Science and Technology","issn_l":"2615-9015","issn":["2615-9015"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I3020192730","host_organization_name":"Tr\u01b0\u1eddng \u0110H Nguy\u1ec5n T\u1ea5t Th\u00e0nh","host_organization_lineage":["https://openalex.org/I3020192730"],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Science and Technology","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://jstdata.ntt.edu.vn/index.php/jst/article/download/1119/941","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121682151","display_name":"Bao Quoc Nguyen","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen Bao Quoc","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067659457","display_name":"B\u00f9i V\u0169 Minh","orcid":"https://orcid.org/0000-0003-0222-166X","observed_orcids":["https://orcid.org/0000-0003-0222-166X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bui Vu Minh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160072901","display_name":"Ho A Lil","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I3020192730","display_name":"Tr\u01b0\u1eddng \u0110H Nguy\u1ec5n T\u1ea5t Th\u00e0nh","ror":"https://ror.org/04r9s1v23","country_code":"VN","type":"education","lineage":["https://openalex.org/I3020192730"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Ho A Lil","raw_affiliation_strings":["Faculty of Engineering and Technology , Nguyen Tat Thanh University , Ho Chi Minh City , Viet Nam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Technology , Nguyen Tat Thanh University , Ho Chi Minh City , Viet Nam","institution_ids":["https://openalex.org/I3020192730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047970861","display_name":"Lam Hoang Cat Tien","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lam Hoang Cat Tien","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5093984622","display_name":"Tr\u1ea7n Ng\u1ecdc Huy Th\u1ecbnh","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tran Ngoc Huy Thinh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82036157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"10","first_page":"70","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9990000128746033,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.0008999999845400453,"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/T10468","display_name":"Photovoltaic System Optimization Techniques","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/short-term-photovoltaic-power-forecasting","display_name":"short-term photovoltaic power forecasting","score":0.9580000042915344},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.9449999928474426},{"id":"https://openalex.org/keywords/edge-computing","display_name":"edge computing","score":0.5389999747276306},{"id":"https://openalex.org/keywords/model-compression","display_name":"model compression","score":0.6129999756813049},{"id":"https://openalex.org/keywords/shap","display_name":"SHAP","score":0.7480000257492065},{"id":"https://openalex.org/keywords/time-series-feature-engineering","display_name":"time-series feature engineering","score":0.8019999861717224},{"id":"https://openalex.org/keywords/correlation-based-feature-selection","display_name":"correlation-based feature selection","score":0.7540000081062317},{"id":"https://openalex.org/keywords/feature-importance","display_name":"feature importance","score":0.8190000057220459},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.6359999775886536},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8349999785423279},{"id":"https://openalex.org/keywords/support-vector-regression","display_name":"support vector regression","score":0.9990000128746033},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.949999988079071},{"id":"https://openalex.org/keywords/resource-constrained-devices","display_name":"resource-constrained devices","score":0.7300000190734863}],"concepts":[{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.7975000143051147},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7540000081062317},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6564000248908997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5884000062942505},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5819000005722046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5623999834060669},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5620999932289124},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4749000072479248},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46939998865127563},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4163999855518341},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30869999527931213},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2937000095844269},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.28130000829696655},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2565999925136566}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.55401/vj84sp67","doi":"https://doi.org/10.55401/vj84sp67","is_oa":true,"landing_page_url":"https://doi.org/10.55401/vj84sp67","pdf_url":"https://jstdata.ntt.edu.vn/index.php/jst/article/download/1119/941","source":{"id":"https://openalex.org/S4220651663","display_name":"Journal of Science and Technology","issn_l":"2615-9015","issn":["2615-9015"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I3020192730","host_organization_name":"Tr\u01b0\u1eddng \u0110H Nguy\u1ec5n T\u1ea5t Th\u00e0nh","host_organization_lineage":["https://openalex.org/I3020192730"],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Science and Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.55401/vj84sp67","doi":"https://doi.org/10.55401/vj84sp67","is_oa":true,"landing_page_url":"https://doi.org/10.55401/vj84sp67","pdf_url":"https://jstdata.ntt.edu.vn/index.php/jst/article/download/1119/941","source":{"id":"https://openalex.org/S4220651663","display_name":"Journal of Science and Technology","issn_l":"2615-9015","issn":["2615-9015"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I3020192730","host_organization_name":"Tr\u01b0\u1eddng \u0110H Nguy\u1ec5n T\u1ea5t Th\u00e0nh","host_organization_lineage":["https://openalex.org/I3020192730"],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.878000020980835,"display_name":"Affordable and clean energy"},{"id":"https://metadata.un.org/sdg/9","score":0.7207000255584717,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224550102.pdf","grobid_xml":"https://content.openalex.org/works/W7224550102.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W3047580138","https://openalex.org/W4312477837","https://openalex.org/W4392101288","https://openalex.org/W4400111503","https://openalex.org/W4406983100","https://openalex.org/W4413009126","https://openalex.org/W4413773348","https://openalex.org/W7141702362"],"related_works":["https://openalex.org/W4409561654","https://openalex.org/W3021683184","https://openalex.org/W7165190531","https://openalex.org/W4411233801","https://openalex.org/W4404068626","https://openalex.org/W4312477837","https://openalex.org/W7222592381","https://openalex.org/W3026127427","https://openalex.org/W7156011826","https://openalex.org/W4403571673"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,15,117],"machine":[4],"learning":[5],"framework":[6,115],"for":[7,19,120,128],"short-term":[8],"photovoltaic":[9,58,125],"power":[10,59],"forecasting,":[11],"aiming":[12],"to":[13,65,77,110],"develop":[14],"tiny":[16],"model":[17,86,99,104],"suitable":[18],"low-cost":[20],"edge":[21],"devices":[22],"while":[23,61,84],"maintaining":[24],"accuracy.":[25],"The":[26,113],"methodology":[27],"integrates":[28],"data":[29],"preprocessing,":[30],"time-series":[31],"feature":[32,34,40,67],"engineering,":[33],"selection":[35],"based":[36],"on":[37],"correlation":[38],"and":[39,42,50,94,98,123],"importance,":[41],"performance":[43,83],"evaluation":[44],"of":[45],"ANN,":[46],"Random":[47],"Forest,":[48],"SVR,":[49],"XGBoost.":[51],"Forecasting":[52],"errors":[53],"are":[54],"analyzed":[55],"across":[56],"different":[57],"ranges,":[60],"SHAP":[62],"is":[63],"used":[64],"interpret":[66],"contributions.":[68],"Results":[69],"show":[70],"that":[71],"reducing":[72,85],"input":[73],"features":[74],"from":[75,107],"15":[76],"7":[78],"(53.3%)":[79],"maintains":[80],"comparable":[81],"forecasting":[82,92,126],"complexity.":[87],"ANN":[88],"achieves":[89],"the":[90],"best":[91],"accuracy":[93,97],"trade-off":[95],"between":[96],"size,":[100],"with":[101],"its":[102],"trained":[103],"size":[105],"decreasing":[106],"82.80":[108],"KB":[109],"70.37":[111],"KB.":[112],"proposed":[114],"provides":[116],"practical":[118],"approach":[119],"developing":[121],"compact":[122],"accurate":[124],"models":[127],"resource-constrained":[129],"Edge":[130],"platforms.":[131]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-10-30T00:00:00"}