{"id":"https://openalex.org/W4408862620","doi":"https://doi.org/10.1109/icca62237.2024.10928074","title":"Comprehensive Forecasting of Smart Grid Stability Using Advanced Deep Learning and Machine Learning Models","display_name":"Comprehensive Forecasting of Smart Grid Stability Using Advanced Deep Learning and Machine Learning Models","publication_year":2024,"publication_date":"2024-12-17","ids":{"openalex":"https://openalex.org/W4408862620","doi":"https://doi.org/10.1109/icca62237.2024.10928074"},"language":"en","primary_location":{"id":"doi:10.1109/icca62237.2024.10928074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca62237.2024.10928074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Computer and Applications (ICCA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5108946654","display_name":"Snigdha Zaman","orcid":null},"institutions":[{"id":"https://openalex.org/I157669161","display_name":"International Islamic University Chittagong","ror":"https://ror.org/00eda4j42","country_code":"BD","type":"education","lineage":["https://openalex.org/I157669161"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Snigdha Zaman","raw_affiliation_strings":["International Islamic University Chittagong,Department of Computer Science and Engineering,Chittagong,Bangladesh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Islamic University Chittagong,Department of Computer Science and Engineering,Chittagong,Bangladesh","institution_ids":["https://openalex.org/I157669161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111210482","display_name":"Abdullah Hafez Nur","orcid":"https://orcid.org/0009-0008-8952-7656"},"institutions":[{"id":"https://openalex.org/I157669161","display_name":"International Islamic University Chittagong","ror":"https://ror.org/00eda4j42","country_code":"BD","type":"education","lineage":["https://openalex.org/I157669161"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Abdullah Hafez Nur","raw_affiliation_strings":["International Islamic University Chittagong,Department of Electronic and Telecommunication Engineering,Chittagong,Bangladesh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Islamic University Chittagong,Department of Electronic and Telecommunication Engineering,Chittagong,Bangladesh","institution_ids":["https://openalex.org/I157669161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027334588","display_name":"Usman Butt","orcid":"https://orcid.org/0000-0002-1703-8756"},"institutions":[{"id":"https://openalex.org/I193260172","display_name":"British University in Dubai","ror":"https://ror.org/00mc18523","country_code":"AE","type":"education","lineage":["https://openalex.org/I193260172"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Usman Butt","raw_affiliation_strings":["Cyber Security The British University in Dubai,Cyber Security,Dubai,United Arab Emirates"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cyber Security The British University in Dubai,Cyber Security,Dubai,United Arab Emirates","institution_ids":["https://openalex.org/I193260172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006756424","display_name":"Rejwan Bin Sulaiman","orcid":"https://orcid.org/0000-0002-3037-7808"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rejwan Bin Sulaiman","raw_affiliation_strings":["Northumbria University,Department of Computer Science &#x0026; Technology,Northumbria,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northumbria University,Department of Computer Science &#x0026; Technology,Northumbria,United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054957980","display_name":"Maruf Farhan","orcid":"https://orcid.org/0000-0002-9247-411X"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maruf Farhan","raw_affiliation_strings":["Northumbria University,Department of Computer Science and Engineering,Northumbria,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northumbria University,Department of Computer Science and Engineering,Northumbria,United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9271,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77611391,"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":"01","last_page":"07"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9872999787330627,"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":0.9872999787330627,"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/computer-science","display_name":"Computer science","score":0.7294480800628662},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.6763871908187866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5802925825119019},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5599772930145264},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5425252914428711},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.42212027311325073},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.4108675420284271},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13239532709121704},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06084519624710083}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7294480800628662},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.6763871908187866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5802925825119019},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5599772930145264},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5425252914428711},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.42212027311325073},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.4108675420284271},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13239532709121704},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06084519624710083},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icca62237.2024.10928074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca62237.2024.10928074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Computer and Applications (ICCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2767172243","https://openalex.org/W2919779311","https://openalex.org/W2990261200","https://openalex.org/W3009311085","https://openalex.org/W3011349791","https://openalex.org/W3091939691","https://openalex.org/W3109256480","https://openalex.org/W3127211569","https://openalex.org/W3127698769","https://openalex.org/W3147059732","https://openalex.org/W3171645484","https://openalex.org/W4211109892","https://openalex.org/W4297539676","https://openalex.org/W4366986563","https://openalex.org/W4377819233","https://openalex.org/W4381251851","https://openalex.org/W4390096897","https://openalex.org/W4391023290","https://openalex.org/W4391429045","https://openalex.org/W4391850788","https://openalex.org/W4391851463","https://openalex.org/W4399686954","https://openalex.org/W6847115377"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2751256511","https://openalex.org/W2611989081","https://openalex.org/W1597785538","https://openalex.org/W2382521298","https://openalex.org/W2731899572","https://openalex.org/W2491804929","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4380075502"],"abstract_inverted_index":{"This":[0,131,165],"study":[1],"comprehensively":[2],"examines":[3],"the":[4,8,78,85,105,141,147,156,175,202,205],"ability":[5],"to":[6,154,192],"forecast":[7],"stability":[9,163,176,214],"of":[10,56,77,92,137,150,160,177,184,204],"smart":[11,161,178],"grids":[12],"using":[13,140],"sophisticated":[14],"deep":[15,151,170],"learning":[16,19,152,171],"and":[17,39,69,95,103,114,128,158,187],"machine":[18],"models.":[20],"We":[21],"investigate":[22],"different":[23],"approaches,":[24],"such":[25,64],"as":[26,65],"Bidirectional":[27],"Gated":[28],"Recurrent":[29],"Unit":[30],"(BiGRU),":[31],"Multi-Layer":[32],"Perceptron":[33],"with":[34,49],"Extreme":[35],"Learning":[36],"Machine":[37],"(MLP-ELM),":[38],"innovative":[40],"fusion":[41],"models":[42,58],"that":[43,124],"combine":[44],"Artificial":[45],"Neural":[46],"Networks":[47],"(ANN)":[48],"Support":[50],"Vector":[51],"Machines":[52],"(SVM).":[53],"The":[54,71,116,144],"performance":[55,190],"these":[57],"was":[59],"evaluated":[60],"by":[61],"comparing":[62],"parameters":[63],"accuracy,":[66],"precision,":[67],"recall,":[68],"F-measure.":[70],"dataset":[72],"is":[73],"an":[74],"improved":[75],"version":[76],"Electrical":[79],"Grid":[80],"Stability":[81],"Simulated":[82],"Dataset":[83],"from":[84],"Karlsruher":[86],"Institut":[87],"f\u00fcr":[88],"Technologie.":[89],"It":[90],"consists":[91],"60,000":[93],"observations":[94],"includes":[96],"twelve":[97],"primary":[98],"prediction":[99,182],"variables.":[100],"Before":[101],"training":[102],"testing":[104,196],"models,":[106],"we":[107,118],"conducted":[108],"thorough":[109],"exploratory":[110],"data":[111],"analysis":[112],"(EDA)":[113],"preprocessing.":[115],"solution":[117],"present":[119],"utilizes":[120],"a":[121,134,168,181],"Sequential":[122],"model":[123],"incorporates":[125],"multiple":[126],"optimizers":[127],"activation":[129],"functions.":[130],"approach":[132],"achieves":[133],"maximum":[135],"accuracy":[136,183],"99.48%":[138],"when":[139],"Adamax":[142],"optimizer.":[143],"results":[145],"indicate":[146],"substantial":[148],"capacity":[149],"methods":[153],"improve":[155],"dependability":[157],"effectiveness":[159,203],"grid":[162,199],"forecasts.":[164,215],"work":[166],"offers":[167],"novel":[169],"methodology":[172],"for":[173,212],"predicting":[174],"grids,":[179],"attaining":[180],"99.48":[185],"%":[186],"exhibiting":[188],"enhanced":[189],"relative":[191],"leading":[193],"methodologies.":[194],"Comprehensive":[195],"across":[197],"several":[198],"settings":[200],"demonstrates":[201],"proposed":[206],"tactics,":[207],"rendering":[208],"it":[209],"very":[210],"beneficial":[211],"real-time":[213]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
