{"id":"https://openalex.org/W3080683114","doi":"https://doi.org/10.1016/j.patcog.2020.107617","title":"Implementing transfer learning across different datasets for time series forecasting","display_name":"Implementing transfer learning across different datasets for time series forecasting","publication_year":2020,"publication_date":"2020-08-25","ids":{"openalex":"https://openalex.org/W3080683114","doi":"https://doi.org/10.1016/j.patcog.2020.107617","mag":"3080683114"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.patcog.2020.107617","pdf_url":null,"source":{"id":"https://openalex.org/S414566","display_name":"Pattern Recognition","issn_l":"0031-3203","issn":["0031-3203","1873-5142"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5100728766","display_name":"Rui Ye","orcid":"https://orcid.org/0009-0007-5998-8200"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"funder","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Ye","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, #29, Jiang Jun road, Nanjing 211106, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, #29, Jiang Jun road, Nanjing 211106, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008891189","display_name":"Qun Dai","orcid":"https://orcid.org/0000-0003-4618-7299"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"funder","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qun Dai","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, #29, Jiang Jun road, Nanjing 211106, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, #29, Jiang Jun road, Nanjing 211106, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5008891189"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":{"value":2710,"currency":"USD","value_usd":2710},"apc_paid":null,"fwci":8.181,"has_fulltext":false,"cited_by_count":93,"citation_normalized_percentile":{"value":0.999771,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"109","issue":null,"first_page":"107617","last_page":"107617"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9993,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9993,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9781,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9747,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7424896},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.736368},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic Time Warping","score":0.65917784}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8551637},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7424896},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.736368},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.66657203},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.65917784},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5864715},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.56009805},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.52104324},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45678458},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43219656},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4208255},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.patcog.2020.107617","pdf_url":null,"source":{"id":"https://openalex.org/S414566","display_name":"Pattern Recognition","issn_l":"0031-3203","issn":["0031-3203","1873-5142"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61473150"}],"datasets":[],"versions":[],"referenced_works_count":30,"referenced_works":["https://openalex.org/W1973058638","https://openalex.org/W1976608515","https://openalex.org/W1977945115","https://openalex.org/W2016210396","https://openalex.org/W2058819127","https://openalex.org/W2064675550","https://openalex.org/W2091921805","https://openalex.org/W2094808762","https://openalex.org/W2120559187","https://openalex.org/W2133573607","https://openalex.org/W2157331557","https://openalex.org/W2594899909","https://openalex.org/W2603648311","https://openalex.org/W2604847698","https://openalex.org/W2726644461","https://openalex.org/W2770501762","https://openalex.org/W2803462565","https://openalex.org/W2894821558","https://openalex.org/W2898843852","https://openalex.org/W2906204361","https://openalex.org/W2943547402","https://openalex.org/W2945328857","https://openalex.org/W2951670162","https://openalex.org/W2962752580","https://openalex.org/W2964288524","https://openalex.org/W2966607134","https://openalex.org/W2970658101","https://openalex.org/W2994941150","https://openalex.org/W398859631","https://openalex.org/W4376523873"],"related_works":["https://openalex.org/W4290188444","https://openalex.org/W3183901164","https://openalex.org/W3176438653","https://openalex.org/W3167935049","https://openalex.org/W3135818718","https://openalex.org/W3127975138","https://openalex.org/W3092399163","https://openalex.org/W3003905048","https://openalex.org/W2609942398","https://openalex.org/W2253429366"],"abstract_inverted_index":null,"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3080683114","counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-04-05T03:09:24.720329","created_date":"2020-09-01"}