{"id":"https://openalex.org/W2771192076","doi":"https://doi.org/10.1109/ssd.2017.8166997","title":"Photovoltaic power forecasting using reccurent neural networks","display_name":"Photovoltaic power forecasting using reccurent neural networks","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2771192076","doi":"https://doi.org/10.1109/ssd.2017.8166997","mag":"2771192076"},"language":"en","primary_location":{"id":"doi:10.1109/ssd.2017.8166997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd.2017.8166997","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 14th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","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/A5002854034","display_name":"Rim Ben Ammar","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Rim Ben Ammar","raw_affiliation_strings":["Dept. Electrical Engineering, National Engineering School of Sfax, Sfax, Tunisia"],"affiliations":[{"raw_affiliation_string":"Dept. Electrical Engineering, National Engineering School of Sfax, Sfax, Tunisia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002124373","display_name":"Abdelmajid Oualha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abdelmajid Oualha","raw_affiliation_strings":["Dept. Electrical Engineering, National Engineering School of Sfax, Sfax, Tunisia"],"affiliations":[{"raw_affiliation_string":"Dept. Electrical Engineering, National Engineering School of Sfax, Sfax, Tunisia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5002854034"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.39,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71746155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"537","last_page":"544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9991000294685364,"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":0.9894000291824341,"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/photovoltaic-system","display_name":"Photovoltaic system","score":0.7330840229988098},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7181382775306702},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.7086878418922424},{"id":"https://openalex.org/keywords/power-grid","display_name":"Power grid","score":0.5073179602622986},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4870891571044922},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.4805174767971039},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.480010449886322},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47431325912475586},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.46950483322143555},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.45077869296073914},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.4292770326137543},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3349541425704956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28616926074028015},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2471579909324646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24262192845344543},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22817835211753845},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.16889038681983948},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15053784847259521}],"concepts":[{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.7330840229988098},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7181382775306702},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7086878418922424},{"id":"https://openalex.org/C2983254600","wikidata":"https://www.wikidata.org/wiki/Q1096907","display_name":"Power grid","level":3,"score":0.5073179602622986},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4870891571044922},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.4805174767971039},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.480010449886322},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47431325912475586},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.46950483322143555},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.45077869296073914},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.4292770326137543},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3349541425704956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28616926074028015},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2471579909324646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24262192845344543},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22817835211753845},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.16889038681983948},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15053784847259521},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/ssd.2017.8166997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd.2017.8166997","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 14th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.6299999952316284,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1507040636","https://openalex.org/W1513907279","https://openalex.org/W2019091079","https://openalex.org/W2028782916","https://openalex.org/W2045320154","https://openalex.org/W2053533577","https://openalex.org/W2070826863","https://openalex.org/W2103144999","https://openalex.org/W2106817714","https://openalex.org/W2205897359","https://openalex.org/W2316949790","https://openalex.org/W2500192993","https://openalex.org/W6630986038"],"related_works":["https://openalex.org/W4318676890","https://openalex.org/W2039947585","https://openalex.org/W4385195237","https://openalex.org/W3178576217","https://openalex.org/W4285102093","https://openalex.org/W4210644201","https://openalex.org/W3111532652","https://openalex.org/W2510451507","https://openalex.org/W4283367183","https://openalex.org/W4381189085"],"abstract_inverted_index":{"The":[0,112],"variability":[1],"of":[2,44,76,88,115,129],"the":[3,8,19,53,58,62,73,86,89,93,96,99,104,116,121,126,130,135,143,146],"Photovoltaic":[4],"power,":[5],"due":[6],"to":[7,26],"ever-changing":[9],"weather":[10],"conditions,":[11],"induces":[12],"many":[13],"difficulties":[14],"in":[15],"grid":[16,28],"management.":[17],"Thus,":[18],"PV":[20,46],"power":[21,41],"prediction":[22],"becomes":[23],"highly":[24],"recommended":[25],"ensure":[27],"stability":[29],"and":[30,39,57,92,98,125,145],"service":[31],"continuity.":[32],"This":[33],"paper":[34],"presented":[35],"daily,":[36],"monthly,":[37],"weekly":[38],"yearly":[40],"output":[42],"forecasting":[43],"a":[45,79],"system":[47],"using":[48],"recurrent":[49],"neural":[50,138],"networks":[51,91],"namely":[52],"modified":[54,136],"Elman,":[55],"Jordan":[56,144],"hybrid":[59,147],"model":[60],"combining":[61],"latest":[63],"techniques.":[64],"They":[65],"were":[66],"trained":[67],"based":[68],"on":[69],"past":[70],"data":[71],"from":[72],"National":[74],"Institute":[75],"Meteorology":[77],"adopting":[78],"standard":[80],"back":[81],"propagation":[82],"algorithm.":[83],"After":[84],"training,":[85],"test":[87],"different":[90],"comparison":[94],"between":[95,107],"predicted":[97],"measured":[100],"powers":[101],"showed":[102],"that":[103,134],"average":[105],"error":[106],"them":[108],"doesn't":[109],"exceed":[110],"8%.":[111],"lowest":[113],"percentages":[114,128],"Root":[117],"Mean":[118,122],"Squared":[119],"Error,":[120],"Absolute":[123],"Error":[124],"highest":[127],"Correlation":[131],"Factor":[132],"proved":[133],"Elman":[137],"network":[139],"performed":[140],"better":[141],"than":[142],"networks.":[148]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
