{"id":"https://openalex.org/W2550324762","doi":"https://doi.org/10.1109/ijcnn.2016.7727239","title":"Identification of minimal timespan problem for recurrent neural networks with application to cyclone wind-intensity prediction","display_name":"Identification of minimal timespan problem for recurrent neural networks with application to cyclone wind-intensity prediction","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2550324762","doi":"https://doi.org/10.1109/ijcnn.2016.7727239","mag":"2550324762"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5045891783","display_name":"Ratneel Deo","orcid":"https://orcid.org/0000-0003-3801-8612"},"institutions":[{"id":"https://openalex.org/I44666525","display_name":"University of the South Pacific","ror":"https://ror.org/008stv805","country_code":"FJ","type":"education","lineage":["https://openalex.org/I44666525"]}],"countries":["FJ"],"is_corresponding":true,"raw_author_name":"Ratneel Deo","raw_affiliation_strings":["Artificial Intelligence and Cybernetics Research Group Software Foundation, Nausori, Fiji","School of Computing Information and Mathematical Sciences, University of South Pacific, Suva, Fiji"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence and Cybernetics Research Group Software Foundation, Nausori, Fiji","institution_ids":[]},{"raw_affiliation_string":"School of Computing Information and Mathematical Sciences, University of South Pacific, Suva, Fiji","institution_ids":["https://openalex.org/I44666525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043246042","display_name":"Rohitash Chandra","orcid":"https://orcid.org/0000-0001-6353-1464"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohitash Chandra","raw_affiliation_strings":["Artificial Intelligence and Cybernetics Research Group Software Foundation, Nausori, Fiji"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence and Cybernetics Research Group Software Foundation, Nausori, Fiji","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045891783"],"corresponding_institution_ids":["https://openalex.org/I44666525"],"apc_list":null,"apc_paid":null,"fwci":1.2269,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79401046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"14","issue":null,"first_page":"489","last_page":"496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11483","display_name":"Tropical and Extratropical Cyclones Research","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"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/T11483","display_name":"Tropical and Extratropical Cyclones Research","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"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/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"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":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6713662147521973},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5781388282775879},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.572142481803894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4957238435745239},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47835037112236023},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.47148844599723816},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.4518342912197113},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4440211057662964},{"id":"https://openalex.org/keywords/tropical-cyclone","display_name":"Tropical cyclone","score":0.41690096259117126},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3875938951969147},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.24202293157577515},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07457643747329712}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6713662147521973},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5781388282775879},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.572142481803894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4957238435745239},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47835037112236023},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.47148844599723816},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.4518342912197113},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4440211057662964},{"id":"https://openalex.org/C29141058","wikidata":"https://www.wikidata.org/wiki/Q8092","display_name":"Tropical cyclone","level":2,"score":0.41690096259117126},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3875938951969147},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.24202293157577515},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07457643747329712},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.75}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W160383300","https://openalex.org/W1522932718","https://openalex.org/W1549386224","https://openalex.org/W1555689267","https://openalex.org/W1558675754","https://openalex.org/W1567983960","https://openalex.org/W1639305354","https://openalex.org/W1969988238","https://openalex.org/W1980986928","https://openalex.org/W1987912102","https://openalex.org/W1988518729","https://openalex.org/W2023260243","https://openalex.org/W2050964340","https://openalex.org/W2066796814","https://openalex.org/W2067562186","https://openalex.org/W2072782187","https://openalex.org/W2076977109","https://openalex.org/W2086173776","https://openalex.org/W2110371102","https://openalex.org/W2120772369","https://openalex.org/W2148067905","https://openalex.org/W2150355110","https://openalex.org/W2172198266","https://openalex.org/W2180096630","https://openalex.org/W2997026295","https://openalex.org/W4214843733","https://openalex.org/W4254816979","https://openalex.org/W6681804199"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3032952384","https://openalex.org/W3034302643","https://openalex.org/W1847088711","https://openalex.org/W4225394202","https://openalex.org/W3036642985","https://openalex.org/W2964335273","https://openalex.org/W1889624880","https://openalex.org/W4315556926"],"abstract_inverted_index":{"Time":[0],"series":[1],"prediction":[2,24,48,70,99,136],"relies":[3],"on":[4,64],"past":[5,15,114],"data":[6,16,35],"points":[7,17,36],"to":[8,50,97,130],"make":[9],"robust":[10,69],"predictions.":[11],"The":[12,117],"span":[13],"of":[14,33,100,133],"is":[18,37,40,56,124,149],"important":[19,126],"for":[20,43,68,82],"some":[21],"applications":[22],"since":[23],"will":[25],"not":[26],"be":[27,51,141],"possible":[28],"unless":[29],"the":[30,34,98,101,110,131,146],"minimal":[31,65,122,147],"timespan":[32,66,123,148],"available.":[38],"This":[39,58],"a":[41,54,121],"problem":[42],"cyclone":[44,55],"wind-intensity":[45],"prediction,":[46],"where":[47],"needs":[49],"made":[52],"as":[53],"identified.":[57],"paper":[59],"presents":[60],"an":[61,125],"empirical":[62],"study":[63],"required":[67],"using":[71],"Elman":[72,84],"recurrent":[73,85],"neural":[74],"networks.":[75],"Two":[76],"different":[77],"training":[78,83],"methods":[79],"are":[80,95],"evaluated":[81],"network":[86],"that":[87,106,120,128],"includes":[88],"cooperative":[89],"coevolution":[90],"and":[91,138],"backpropagation-though":[92],"time.":[93],"They":[94],"applied":[96],"wind":[102],"intensity":[103],"in":[104,109,135,143],"cyclones":[105],"took":[107],"place":[108],"South":[111],"Pacific":[112],"over":[113],"few":[115],"decades.":[116],"results":[118],"show":[119],"factor":[127],"leads":[129],"measure":[132],"robustness":[134],"performance":[137],"strategies":[139],"should":[140],"taken":[142],"cases":[144],"when":[145],"needed.":[150]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}