{"id":"https://openalex.org/W4390612216","doi":"https://doi.org/10.1007/s00500-023-09531-9","title":"A Bi-GRU-based encoder\u2013decoder framework for multivariate time series forecasting","display_name":"A Bi-GRU-based encoder\u2013decoder framework for multivariate time series forecasting","publication_year":2024,"publication_date":"2024-01-05","ids":{"openalex":"https://openalex.org/W4390612216","doi":"https://doi.org/10.1007/s00500-023-09531-9"},"language":"en","primary_location":{"id":"doi:10.1007/s00500-023-09531-9","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00500-023-09531-9","pdf_url":null,"source":{"id":"https://openalex.org/S65753830","display_name":"Soft Computing","issn_l":"1432-7643","issn":["1432-7643","1433-7479"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Soft Computing","raw_type":"journal-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/A5046751676","display_name":"Hanen Balti","orcid":"https://orcid.org/0000-0003-2725-226X"},"institutions":[{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Hanen Balti","raw_affiliation_strings":["Riadi Laboratory,ENSI, University of Manouba, 2010, Manouba, Tunisia"],"raw_orcid":"https://orcid.org/0000-0003-2725-226X","affiliations":[{"raw_affiliation_string":"Riadi Laboratory,ENSI, University of Manouba, 2010, Manouba, Tunisia","institution_ids":["https://openalex.org/I83259278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073221047","display_name":"Ali Ben Abbes","orcid":"https://orcid.org/0000-0001-5714-7562"},"institutions":[{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Ali Ben Abbes","raw_affiliation_strings":["Riadi Laboratory,ENSI, University of Manouba, 2010, Manouba, Tunisia"],"raw_orcid":"https://orcid.org/0000-0001-5714-7562","affiliations":[{"raw_affiliation_string":"Riadi Laboratory,ENSI, University of Manouba, 2010, Manouba, Tunisia","institution_ids":["https://openalex.org/I83259278"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053542801","display_name":"Imed Riadh Farah","orcid":"https://orcid.org/0000-0001-9114-5659"},"institutions":[{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Imed Riadh Farah","raw_affiliation_strings":["Riadi Laboratory,ENSI, University of Manouba, 2010, Manouba, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Riadi Laboratory,ENSI, University of Manouba, 2010, Manouba, Tunisia","institution_ids":["https://openalex.org/I83259278"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5046751676"],"corresponding_institution_ids":["https://openalex.org/I83259278"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":null,"fwci":7.694,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.98096169,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"28","issue":"9-10","first_page":"6775","last_page":"6786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10029","display_name":"Climate variability and models","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.790289044380188},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.7741766571998596},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.7675968408584595},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7294634580612183},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6161622405052185},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5706208348274231},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.525469183921814},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5136396288871765},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5082690119743347},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4476626217365265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44028639793395996},{"id":"https://openalex.org/keywords/multivariate-analysis","display_name":"Multivariate analysis","score":0.43638840317726135},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4033791124820709},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3902393579483032},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3527398705482483},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.32815027236938477},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26577121019363403},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2502206265926361},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0656687319278717}],"concepts":[{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.790289044380188},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.7741766571998596},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7675968408584595},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7294634580612183},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6161622405052185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5706208348274231},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.525469183921814},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5136396288871765},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5082690119743347},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4476626217365265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44028639793395996},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.43638840317726135},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4033791124820709},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3902393579483032},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3527398705482483},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32815027236938477},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26577121019363403},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2502206265926361},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0656687319278717},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s00500-023-09531-9","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00500-023-09531-9","pdf_url":null,"source":{"id":"https://openalex.org/S65753830","display_name":"Soft Computing","issn_l":"1432-7643","issn":["1432-7643","1433-7479"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Soft Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2077968790","https://openalex.org/W2106595237","https://openalex.org/W2528639018","https://openalex.org/W2572939427","https://openalex.org/W2592453717","https://openalex.org/W2737431556","https://openalex.org/W2747599906","https://openalex.org/W2779580338","https://openalex.org/W2889283791","https://openalex.org/W2898791292","https://openalex.org/W2928248204","https://openalex.org/W2930650313","https://openalex.org/W2948490758","https://openalex.org/W2952335866","https://openalex.org/W2953601905","https://openalex.org/W2963608065","https://openalex.org/W2991499610","https://openalex.org/W3000499162","https://openalex.org/W3008663956","https://openalex.org/W3011434025","https://openalex.org/W3082044521","https://openalex.org/W3095242808","https://openalex.org/W3185100125","https://openalex.org/W3189269126","https://openalex.org/W3196721192","https://openalex.org/W3202254272","https://openalex.org/W3203749690","https://openalex.org/W4220712276","https://openalex.org/W4223929908","https://openalex.org/W4323074868"],"related_works":["https://openalex.org/W3135881084","https://openalex.org/W2380590035","https://openalex.org/W2351712633","https://openalex.org/W4224133501","https://openalex.org/W1828158523","https://openalex.org/W2047547195","https://openalex.org/W4388984322","https://openalex.org/W4285509495","https://openalex.org/W39712736","https://openalex.org/W2045832042"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":12}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
