{"id":"https://openalex.org/W4200273761","doi":"https://doi.org/10.1145/3490725.3490747","title":"Additional time series features for preciseness improvement of LSTM-based COVID-19 spread forecasting model","display_name":"Additional time series features for preciseness improvement of LSTM-based COVID-19 spread forecasting model","publication_year":2021,"publication_date":"2021-09-17","ids":{"openalex":"https://openalex.org/W4200273761","doi":"https://doi.org/10.1145/3490725.3490747"},"language":"en","primary_location":{"id":"doi:10.1145/3490725.3490747","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490725.3490747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Machine Learning and Machine Intelligence","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/A5030946149","display_name":"Tossapon Nuanchuay","orcid":null},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Tossapon Nuanchuay","raw_affiliation_strings":["Department of Computer Engineering, Chulalongkorn University, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Chulalongkorn University, Thailand","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076276278","display_name":"Sukree Sinthupinyo","orcid":"https://orcid.org/0009-0004-6079-6415"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Sukree Sinthupinyo","raw_affiliation_strings":["Department of Computer Engineering, Chulalongkorn University, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Chulalongkorn University, Thailand","institution_ids":["https://openalex.org/I158708052"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030946149"],"corresponding_institution_ids":["https://openalex.org/I158708052"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.14450985,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"145","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.993399977684021,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.8234459757804871},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6848105788230896},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6183490753173828},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5410283207893372},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.5237436294555664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49247464537620544},{"id":"https://openalex.org/keywords/2019-20-coronavirus-outbreak","display_name":"2019-20 coronavirus outbreak","score":0.48963385820388794},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.4643137454986572},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3982439339160919},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.387495219707489},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.33483728766441345},{"id":"https://openalex.org/keywords/outbreak","display_name":"Outbreak","score":0.3199547529220581},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14715182781219482},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06743237376213074},{"id":"https://openalex.org/keywords/virology","display_name":"Virology","score":0.061523884534835815}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.8234459757804871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6848105788230896},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6183490753173828},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5410283207893372},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.5237436294555664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49247464537620544},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.48963385820388794},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.4643137454986572},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3982439339160919},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.387495219707489},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33483728766441345},{"id":"https://openalex.org/C116675565","wikidata":"https://www.wikidata.org/wiki/Q3241045","display_name":"Outbreak","level":2,"score":0.3199547529220581},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14715182781219482},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06743237376213074},{"id":"https://openalex.org/C159047783","wikidata":"https://www.wikidata.org/wiki/Q7215","display_name":"Virology","level":1,"score":0.061523884534835815},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3490725.3490747","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490725.3490747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Machine Learning and Machine Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2885195348","https://openalex.org/W3013530892","https://openalex.org/W3021303430","https://openalex.org/W3022210384","https://openalex.org/W3035592557","https://openalex.org/W3093759246","https://openalex.org/W3096940900","https://openalex.org/W3097257811","https://openalex.org/W3119322032","https://openalex.org/W3120178178","https://openalex.org/W3124027516","https://openalex.org/W3126878744","https://openalex.org/W4285717428"],"related_works":["https://openalex.org/W4200329650","https://openalex.org/W3127156785","https://openalex.org/W4205754011","https://openalex.org/W3009669391","https://openalex.org/W4205215807","https://openalex.org/W3005417802","https://openalex.org/W4226296940","https://openalex.org/W3028835529","https://openalex.org/W3036314732","https://openalex.org/W3134376730"],"abstract_inverted_index":{"The":[0,8],"COVID-19":[1,28,70],"pandemic":[2],"has":[3,12],"spread":[4,29],"rapidly":[5],"since":[6],"2019.":[7],"worldwide":[9],"uncontrollable":[10],"outbreak":[11],"caused":[13],"health":[14],"and":[15,65,83],"economic":[16],"damage.":[17],"Multiple":[18],"deep":[19],"learning":[20],"predictable":[21],"models":[22],"have":[23],"been":[24],"proposed":[25],"to":[26,56,97,100,105],"forecast":[27],"that":[30,48],"can":[31,49],"help":[32],"monitor":[33],"the":[34,109],"situation.":[35],"To":[36],"improve":[37,101],"preciseness":[38],"of":[39,68,80,85],"predicted":[40,60,102],"results,":[41],"we":[42],"propose":[43],"multiple":[44],"time":[45],"series":[46],"variables":[47],"be":[50],"used":[51],"in":[52,88],"LSTM":[53,98,110],"based":[54],"model":[55,99,111],"get":[57],"higher":[58],"accuracy":[59],"results":[61,103],"for":[62],"both":[63],"short":[64],"long":[66],"periods":[67],"time.":[69],"cumulative":[71,81,86],"cases,":[72,74],"new":[73],"5":[75],"days":[76],"simple":[77],"moving":[78],"average":[79,84],"cases":[82,87],"neighboring":[89],"countries":[90],"are":[91],"added":[92],"as":[93],"additional":[94,113],"features":[95,114],"fed":[96],"up":[104],"5%":[106],"better":[107],"than":[108],"without":[112],"on":[115],"7,":[116],"14,":[117],"21,":[118],"28-day":[119],"prediction.":[120]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
