{"id":"https://openalex.org/W7135238589","doi":"https://doi.org/10.1186/s42162-026-00656-3","title":"Explainable AI-driven energy forecasting: A DGMR-based feature extraction and EGST-Net prediction framework for transparent decision-making","display_name":"Explainable AI-driven energy forecasting: A DGMR-based feature extraction and EGST-Net prediction framework for transparent decision-making","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7135238589","doi":"https://doi.org/10.1186/s42162-026-00656-3"},"language":"en","primary_location":{"id":"doi:10.1186/s42162-026-00656-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42162-026-00656-3","pdf_url":null,"source":{"id":"https://openalex.org/S3035173479","display_name":"Energy Informatics","issn_l":"2520-8942","issn":["2520-8942"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Energy Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s42162-026-00656-3","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021791321","display_name":"Swaroopa Rani B","orcid":null},"institutions":[{"id":"https://openalex.org/I38335241","display_name":"National Institute of Technology Raipur","ror":"https://ror.org/02y553197","country_code":"IN","type":"education","lineage":["https://openalex.org/I38335241"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Swaroopa Rani B","raw_affiliation_strings":["Department of Information Technology, National Institute of Technology Raipur, Raipur, 492010, Chhattisgarh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, National Institute of Technology Raipur, Raipur, 492010, Chhattisgarh, India","institution_ids":["https://openalex.org/I38335241"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008809636","display_name":"Chandrashekar Jatoth","orcid":"https://orcid.org/0000-0002-8536-0210"},"institutions":[{"id":"https://openalex.org/I38335241","display_name":"National Institute of Technology Raipur","ror":"https://ror.org/02y553197","country_code":"IN","type":"education","lineage":["https://openalex.org/I38335241"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dr. Chandrashekar Jatoth","raw_affiliation_strings":["Department of Information Technology, National Institute of Technology Raipur, Raipur, 492010, Chhattisgarh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, National Institute of Technology Raipur, Raipur, 492010, Chhattisgarh, India","institution_ids":["https://openalex.org/I38335241"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5092907327","display_name":"Sonti Venu","orcid":null},"institutions":[{"id":"https://openalex.org/I38335241","display_name":"National Institute of Technology Raipur","ror":"https://ror.org/02y553197","country_code":"IN","type":"education","lineage":["https://openalex.org/I38335241"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dr. Sonti Venu","raw_affiliation_strings":["Department of Electrical Engineering, National Institute of Technology Raipur, Raipur, India, Chhatisgarh , 492010"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Institute of Technology Raipur, Raipur, India, Chhatisgarh , 492010","institution_ids":["https://openalex.org/I38335241"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021791321"],"corresponding_institution_ids":["https://openalex.org/I38335241"],"apc_list":{"value":790,"currency":"GBP","value_usd":969},"apc_paid":{"value":790,"currency":"GBP","value_usd":969},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49663648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"1","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":0.9287999868392944,"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":0.9287999868392944,"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":0.013799999840557575,"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/T10603","display_name":"Smart Grid Energy Management","score":0.005900000222027302,"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/interpretability","display_name":"Interpretability","score":0.8644000291824341},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.6291000247001648},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5317999720573425},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.47589999437332153},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.41359999775886536},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.412200003862381},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.40369999408721924},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.3952000141143799},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.3594000041484833}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8644000291824341},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7623999714851379},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6291000247001648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5871000289916992},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5781999826431274},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5317999720573425},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.47589999437332153},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43860000371932983},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.41359999775886536},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.40369999408721924},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.3594000041484833},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.3521000146865845},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34060001373291016},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.2856000065803528},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2849000096321106},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.25940001010894775}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s42162-026-00656-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42162-026-00656-3","pdf_url":null,"source":{"id":"https://openalex.org/S3035173479","display_name":"Energy Informatics","issn_l":"2520-8942","issn":["2520-8942"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Energy Informatics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:608c5077fc854ae8a14a025555b75b51","is_oa":true,"landing_page_url":"https://doaj.org/article/608c5077fc854ae8a14a025555b75b51","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Energy Informatics, Vol 9, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s42162-026-00656-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42162-026-00656-3","pdf_url":null,"source":{"id":"https://openalex.org/S3035173479","display_name":"Energy Informatics","issn_l":"2520-8942","issn":["2520-8942"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Energy Informatics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5263012051582336,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W3194796466","https://openalex.org/W4200036215","https://openalex.org/W4200099800","https://openalex.org/W4200550314","https://openalex.org/W4220877827","https://openalex.org/W4224282610","https://openalex.org/W4281572064","https://openalex.org/W4281989703","https://openalex.org/W4289635928","https://openalex.org/W4293167389","https://openalex.org/W4295788744","https://openalex.org/W4307134796","https://openalex.org/W4309120572","https://openalex.org/W4310154744","https://openalex.org/W4313558932","https://openalex.org/W4318464897","https://openalex.org/W4319159759","https://openalex.org/W4321014819","https://openalex.org/W4321780128","https://openalex.org/W4380878302","https://openalex.org/W4386111983","https://openalex.org/W4386409304","https://openalex.org/W4387259010","https://openalex.org/W4391404874","https://openalex.org/W4400955983","https://openalex.org/W4401477764","https://openalex.org/W4401891568"],"related_works":[],"abstract_inverted_index":{"Transparency":[0,8],"in":[1,9,63,116,133,148,257],"Decision-Making":[2,10],"the":[3,22,30,35,90,149,156,160,170,182,196,205,250,259,264,275],"modern":[4],"energy":[5,37,77,226,271,281],"management":[6,272],"systems,":[7],"requires":[11],"proper":[12],"and":[13,20,44,58,96,107,137,140,174,178,193,215,232,242,269],"understandable":[14],"forecasting":[15,78,217],"models":[16,43,208],"capable":[17,123],"of":[18,25,52,66,89,124,127,159,172,195,213,263,266,277],"controlling":[19],"documenting":[21],"intricate":[23],"dynamics":[24],"consumption":[26],"when":[27],"implemented":[28],"within":[29],"smart":[31,228,280],"grid":[32,229],"scenario.":[33],"However,":[34],"existing":[36],"prediction":[38,211],"techniques,":[39,48],"including":[40],"traditional":[41,206],"statistical":[42],"independent":[45],"deep":[46,186],"learning":[47,53,168,187],"are":[49],"often":[50],"incapable":[51],"a":[54,64,87,97,117,210],"nonlinear":[55],"spatiotemporal":[56,167],"relationship,":[57],"offer":[59],"poor":[60],"interpretability,":[61],"resulting":[62],"reduction":[65],"reliability":[67],"to":[68,80,151,189,225,274],"real-life":[69],"use.":[70],"This":[71],"paper":[72],"proposes":[73],"an":[74,141],"Explainable":[75],"AI-based":[76],"model":[79],"address":[81],"these":[82],"limitations,":[83],"which":[84],"will":[85,223],"be":[86],"combination":[88],"Dynamic":[91],"Gated":[92],"Memory":[93,105],"Refinement":[94],"(DGMR)":[95],"hybrid":[98],"EGST-Net":[99],"framework":[100,154,260],"comprising":[101],"Convolutional":[102],"Long":[103],"Short-Term":[104],"(ConvLSTM)":[106],"Transformer-based":[108],"attention":[109],"models.":[110],"The":[111,198,220],"suggested":[112,221],"method":[113],"is":[114,121,261],"novel":[115],"sense":[118],"that":[119,130,145],"it":[120,237],"adaptably":[122],"refining":[125],"feature":[126,165],"its":[128],"aim":[129],"chooses":[131],"selectively,":[132],"informative":[134],"temporal-spatial":[135],"patterns":[136],"eliminates":[138],"noise,":[139],"attention-driven":[142],"elucidation":[143],"section":[144],"enhances":[146],"intelligibility":[147],"determination":[150],"make":[152,249],"forecasts.The":[153],"conducts":[155],"multi-stage":[157],"processing":[158],"data":[161],"(data":[162],"preprocessing,":[163],"DGMR-based":[164],"extraction,":[166],"with":[169,185,209],"help":[171],"EGST-Net,":[173],"attention-based":[175],"interpretability":[176],"analysis)":[177],"was":[179],"launched":[180],"on":[181],"Python":[183],"environment":[184],"libraries":[188],"provide":[190],"effective":[191],"training":[192],"testing":[194],"model.":[197],"experimental":[199],"findings":[200],"showed":[201],"better":[202],"performance":[203],"than":[204],"baseline":[207],"accuracy":[212],"96%":[214],"little":[216],"error":[218],"scores.":[219],"system":[222],"appeal":[224],"providers,":[227],"operators,":[230],"policymakers,":[231],"other":[233],"industrial":[234],"stakeholders":[235],"as":[236,246,248],"can":[238],"facilitate":[239],"resource":[240],"allocation":[241],"efficient":[243],"demand":[244],"prediction,":[245],"well":[247],"decisions":[251],"made":[252],"by":[253],"AI":[254],"interpretable.":[255],"All":[256],"all,":[258],"part":[262],"achievement":[265],"intelligent,":[267],"transparent,":[268],"scalable":[270],"solutions":[273],"development":[276],"next":[278],"generation":[279],"infrastructures.":[282]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-03-14T00:00:00"}
