{"id":"https://openalex.org/W3031648794","doi":"https://doi.org/10.1109/jstars.2020.2998461","title":"A Deep Learning Method With Merged LSTM Neural Networks for SSHA Prediction","display_name":"A Deep Learning Method With Merged LSTM Neural Networks for SSHA Prediction","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3031648794","doi":"https://doi.org/10.1109/jstars.2020.2998461","mag":"3031648794"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2020.2998461","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.2998461","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09103934.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09103934.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006420025","display_name":"Tao Song","orcid":"https://orcid.org/0000-0002-0130-3340"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Song","raw_affiliation_strings":["College of Computer Science and Technology, China University of Petroleum, Qingdao, China","Faculty of Information Science, Universidad de Madird, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0002-0130-3340","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, China University of Petroleum, Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]},{"raw_affiliation_string":"Faculty of Information Science, Universidad de Madird, Madrid, Spain","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101877699","display_name":"Jingyu Jiang","orcid":"https://orcid.org/0000-0003-4197-0858"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Jiang","raw_affiliation_strings":["College of Computer Science and Technology, China University of Petroleum, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, China University of Petroleum, Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100697102","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-6116-7718"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["School of Marine Science and Technology, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Marine Science and Technology, Tianjin University, Tianjin, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029202675","display_name":"Danya Xu","orcid":"https://orcid.org/0000-0001-9172-4669"},"institutions":[{"id":"https://openalex.org/I4210106122","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","ror":"https://ror.org/00y7mag53","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106122"]},{"id":"https://openalex.org/I4391012567","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)","ror":"https://ror.org/03swgqh13","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012567"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danya Xu","raw_affiliation_strings":["Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, China","institution_ids":["https://openalex.org/I4210106122","https://openalex.org/I4391012567"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5006420025"],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":6.3443,"has_fulltext":true,"cited_by_count":55,"citation_normalized_percentile":{"value":0.97177552,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"2853","last_page":"2860"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9930999875068665,"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/T10230","display_name":"Marine and fisheries research","score":0.9761999845504761,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6917279958724976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6494743824005127},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6339893341064453},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5713142156600952},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5488945245742798},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5340164303779602},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.5226169228553772},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.48512348532676697},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.48171573877334595},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.478903204202652},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.47342899441719055},{"id":"https://openalex.org/keywords/sea-surface-height","display_name":"Sea-surface height","score":0.4452463686466217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43159329891204834},{"id":"https://openalex.org/keywords/sea-surface-temperature","display_name":"Sea surface temperature","score":0.4015212059020996},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21018311381340027},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.11803555488586426}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6917279958724976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6494743824005127},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6339893341064453},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5713142156600952},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5488945245742798},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5340164303779602},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.5226169228553772},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.48512348532676697},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.48171573877334595},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.478903204202652},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.47342899441719055},{"id":"https://openalex.org/C142672198","wikidata":"https://www.wikidata.org/wiki/Q7076157","display_name":"Sea-surface height","level":3,"score":0.4452463686466217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43159329891204834},{"id":"https://openalex.org/C134097258","wikidata":"https://www.wikidata.org/wiki/Q1507383","display_name":"Sea surface temperature","level":2,"score":0.4015212059020996},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21018311381340027},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.11803555488586426},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"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/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2020.2998461","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.2998461","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09103934.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fb7ba9ace51e4a7ba2e0cc4d6fab517e","is_oa":true,"landing_page_url":"https://doaj.org/article/fb7ba9ace51e4a7ba2e0cc4d6fab517e","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":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 2853-2860 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2020.2998461","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.2998461","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09103934.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G1190177820","display_name":null,"funder_award_id":"2016-T2/TIC-2024","funder_id":"https://openalex.org/F4320313831","funder_display_name":"Comunidad de Madrid"},{"id":"https://openalex.org/G1389886589","display_name":null,"funder_award_id":"19CX05003A-7","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2312540740","display_name":null,"funder_award_id":"ZR2019MF012","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2494574696","display_name":null,"funder_award_id":"61672033","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2514995294","display_name":null,"funder_award_id":"61672248","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G2701230112","display_name":null,"funder_award_id":"18CX02152A","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G2927360790","display_name":null,"funder_award_id":"61873281","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G3373644481","display_name":null,"funder_award_id":"61873280","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G3765575229","display_name":null,"funder_award_id":"61672033","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G3952835159","display_name":null,"funder_award_id":"61873281","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4037723416","display_name":null,"funder_award_id":"61873280","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4640394122","display_name":null,"funder_award_id":"61672248","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4738107792","display_name":null,"funder_award_id":"2018YFC1406204","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5131945198","display_name":null,"funder_award_id":"61873280","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5323104073","display_name":null,"funder_award_id":"18CX02152A","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5494411164","display_name":null,"funder_award_id":"61873281","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5792700249","display_name":null,"funder_award_id":"2018YFC1406201","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5893998383","display_name":null,"funder_award_id":"61672033","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5902518250","display_name":null,"funder_award_id":"U1811464","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6018377612","display_name":null,"funder_award_id":"ZR2019MF012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6638739136","display_name":null,"funder_award_id":"61672248","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7608283997","display_name":null,"funder_award_id":"18CX02152A","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8301374862","display_name":null,"funder_award_id":"2018YFC1406204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8452570760","display_name":null,"funder_award_id":"U1811464","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8870393515","display_name":null,"funder_award_id":"ZR2019MF012","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G972861203","display_name":null,"funder_award_id":"2018YFC1406204","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320313831","display_name":"Comunidad de Madrid","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3031648794.pdf","grobid_xml":"https://content.openalex.org/works/W3031648794.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W341853587","https://openalex.org/W1487202328","https://openalex.org/W1522301498","https://openalex.org/W1997532350","https://openalex.org/W2019627954","https://openalex.org/W2045558668","https://openalex.org/W2048792023","https://openalex.org/W2194775991","https://openalex.org/W2281954672","https://openalex.org/W2338479108","https://openalex.org/W2476149555","https://openalex.org/W2612707971","https://openalex.org/W2619995677","https://openalex.org/W2631883531","https://openalex.org/W2682975603","https://openalex.org/W2751432571","https://openalex.org/W2767058493","https://openalex.org/W2777287263","https://openalex.org/W2778580105","https://openalex.org/W2792764867","https://openalex.org/W2886493749","https://openalex.org/W2891424295","https://openalex.org/W2898227364","https://openalex.org/W2963076818","https://openalex.org/W2964121744","https://openalex.org/W2964350391","https://openalex.org/W2995511918","https://openalex.org/W2995676548","https://openalex.org/W2997043451","https://openalex.org/W3101640299","https://openalex.org/W4240485910","https://openalex.org/W6629012617","https://openalex.org/W6631190155","https://openalex.org/W6694260854","https://openalex.org/W6743316907","https://openalex.org/W6745582524","https://openalex.org/W6747795875","https://openalex.org/W6749825310"],"related_works":["https://openalex.org/W4200496917","https://openalex.org/W4385280324","https://openalex.org/W1964842106","https://openalex.org/W3164092017","https://openalex.org/W2912153778","https://openalex.org/W2379582517","https://openalex.org/W4387163678","https://openalex.org/W2384929967","https://openalex.org/W2064608654","https://openalex.org/W1544332598"],"abstract_inverted_index":{"Sea":[0,98],"surface":[1],"height":[2],"anomaly":[3],"(SSHA)":[4],"is":[5,49,57],"an":[6],"elemental":[7],"factor":[8],"in":[9,73,94,159],"ocean":[10],"environment":[11],"and":[12,65,77,120,154],"marine":[13],"engineering.":[14],"Oceanography":[15],"models":[16],"can":[17,68],"forecast":[18],"SSH":[19],"by":[20,123],"data":[21],"simulation,":[22],"but":[23],"the":[24,70,95],"accuracy":[25,106],"decreases":[26],"heavily":[27],"when":[28],"it":[29],"predicts":[30],"a":[31,39,60],"little":[32],"long":[33],"time":[34,61,75,148],"ahead.":[35],"In":[36],"this":[37],"article,":[38],"deep":[40],"learning":[41,139],"method,":[42],"named":[43],"merged-long":[44],"short":[45,74],"term":[46],"memory":[47],"(LSTM),":[48],"proposed":[50,131],"to":[51],"predict":[52],"SSHA.":[53,161],"Specifically,":[54],"SSHA":[55,88],"prediction":[56],"treated":[58],"as":[59],"series":[62,82],"forecasting":[63],"problem,":[64],"our":[66,101],"merged-LSTM":[67],"mine":[69],"discipline":[71],"hidden":[72],"series,":[76],"tackle":[78],"long-term":[79],"dependence":[80],"of":[81,90,110],"changes.":[83],"Data":[84],"experiments":[85],"conducted":[86],"on":[87],"dataset":[89],"China":[91,97],"Ocean":[92],"Reanalysis":[93],"South":[96],"show":[99],"that":[100],"method":[102,132],"achieves":[103],"average":[104],"predicting":[105,160],"plus/minus":[107],"standard":[108],"deviation":[109],"coming":[111],"24":[112],"h,":[113,115,117,119],"48":[114],"72":[116],"96":[118],"120":[121],"h":[122],"90.99\u00b110.56%,":[124],"85.49\u00b113.93%,":[125],"79.99\u00b116.08%,":[126],"74.23\u00b118.05%,":[127],"68.15\u00b118.84%,":[128],"respectively.":[129],"The":[130],"performs":[133],"better":[134],"than":[135],"several":[136],"state-of-the-art":[137],"machine":[138],"methods,":[140],"including":[141],"artificial":[142],"neural":[143,146,157],"network,":[144,147,150],"merged-recurrent":[145],"convolutional":[149,156],"merged-gate":[151],"recurrent":[152],"unit,":[153],"one-dimensional":[155],"network":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}