{"id":"https://openalex.org/W4220907741","doi":"https://doi.org/10.1186/s40537-022-00584-5","title":"Machine learning-based turbulence-risk prediction method for the safe operation of aircrafts","display_name":"Machine learning-based turbulence-risk prediction method for the safe operation of aircrafts","publication_year":2022,"publication_date":"2022-03-07","ids":{"openalex":"https://openalex.org/W4220907741","doi":"https://doi.org/10.1186/s40537-022-00584-5"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-022-00584-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00584-5","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-022-00584-5","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-022-00584-5","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011990657","display_name":"Shinya Mizuno","orcid":"https://orcid.org/0000-0001-6030-3589"},"institutions":[{"id":"https://openalex.org/I85140907","display_name":"Shizuoka Institute of Science and Technology","ror":"https://ror.org/00vq1d511","country_code":"JP","type":"education","lineage":["https://openalex.org/I85140907"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shinya Mizuno","raw_affiliation_strings":["Shizuoka Institute of Science and Technology, 2200-2, Toyosawa, Fukuroi, Shizuoka, 437-8555, Japan"],"raw_orcid":"https://orcid.org/0000-0001-6030-3589","affiliations":[{"raw_affiliation_string":"Shizuoka Institute of Science and Technology, 2200-2, Toyosawa, Fukuroi, Shizuoka, 437-8555, Japan","institution_ids":["https://openalex.org/I85140907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006799091","display_name":"Haruka Ohba","orcid":"https://orcid.org/0009-0007-9772-9197"},"institutions":[{"id":"https://openalex.org/I85140907","display_name":"Shizuoka Institute of Science and Technology","ror":"https://ror.org/00vq1d511","country_code":"JP","type":"education","lineage":["https://openalex.org/I85140907"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haruka Ohba","raw_affiliation_strings":["Shizuoka Institute of Science and Technology, 2200-2, Toyosawa, Fukuroi, Shizuoka, 437-8555, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shizuoka Institute of Science and Technology, 2200-2, Toyosawa, Fukuroi, Shizuoka, 437-8555, Japan","institution_ids":["https://openalex.org/I85140907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102044901","display_name":"Koji Ito","orcid":null},"institutions":[{"id":"https://openalex.org/I146155226","display_name":"J. F. Oberlin University","ror":"https://ror.org/02s5jck73","country_code":"JP","type":"education","lineage":["https://openalex.org/I146155226"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Ito","raw_affiliation_strings":["J.F. Oberlin University, 3758 Tokiwa-machi, Machida-shi, Tokyo, 194-0294, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J.F. Oberlin University, 3758 Tokiwa-machi, Machida-shi, Tokyo, 194-0294, Japan","institution_ids":["https://openalex.org/I146155226"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011990657"],"corresponding_institution_ids":["https://openalex.org/I85140907"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":2.078,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.85458931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"9","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11371","display_name":"Wind and Air Flow Studies","score":0.9914000034332275,"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"}},"topics":[{"id":"https://openalex.org/T11371","display_name":"Wind and Air Flow Studies","score":0.9914000034332275,"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/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9902999997138977,"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/T12125","display_name":"Aerospace and Aviation Technology","score":0.968999981880188,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/turbulence","display_name":"Turbulence","score":0.8626568913459778},{"id":"https://openalex.org/keywords/clear-air-turbulence","display_name":"Clear-air turbulence","score":0.6052917242050171},{"id":"https://openalex.org/keywords/k-epsilon-turbulence-model","display_name":"K-epsilon turbulence model","score":0.4944610595703125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46151280403137207},{"id":"https://openalex.org/keywords/k-omega-turbulence-model","display_name":"K-omega turbulence model","score":0.4385163187980652},{"id":"https://openalex.org/keywords/turbulence-kinetic-energy","display_name":"Turbulence kinetic energy","score":0.42443597316741943},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14348891377449036},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.1339472234249115}],"concepts":[{"id":"https://openalex.org/C196558001","wikidata":"https://www.wikidata.org/wiki/Q190132","display_name":"Turbulence","level":2,"score":0.8626568913459778},{"id":"https://openalex.org/C23379533","wikidata":"https://www.wikidata.org/wiki/Q1099481","display_name":"Clear-air turbulence","level":3,"score":0.6052917242050171},{"id":"https://openalex.org/C150711758","wikidata":"https://www.wikidata.org/wiki/Q17148242","display_name":"K-epsilon turbulence model","level":3,"score":0.4944610595703125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46151280403137207},{"id":"https://openalex.org/C189223162","wikidata":"https://www.wikidata.org/wiki/Q18386383","display_name":"K-omega turbulence model","level":4,"score":0.4385163187980652},{"id":"https://openalex.org/C15476950","wikidata":"https://www.wikidata.org/wiki/Q7854776","display_name":"Turbulence kinetic energy","level":3,"score":0.42443597316741943},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14348891377449036},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.1339472234249115}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-022-00584-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00584-5","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-022-00584-5","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:de07d159bc6645dc9844920061830fab","is_oa":true,"landing_page_url":"https://doaj.org/article/de07d159bc6645dc9844920061830fab","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":"Journal of Big Data, Vol 9, Iss 1, Pp 1-16 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-022-00584-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00584-5","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-022-00584-5","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4220907741.pdf","grobid_xml":"https://content.openalex.org/works/W4220907741.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1663973292","https://openalex.org/W1965067893","https://openalex.org/W1987735184","https://openalex.org/W2018011148","https://openalex.org/W2034609284","https://openalex.org/W2117066788","https://openalex.org/W2127212721","https://openalex.org/W2158158078","https://openalex.org/W2162818540","https://openalex.org/W2572267491","https://openalex.org/W2589339571","https://openalex.org/W2895053826","https://openalex.org/W2989773666","https://openalex.org/W2991112023","https://openalex.org/W3081677703","https://openalex.org/W3092409488","https://openalex.org/W3093599724","https://openalex.org/W3153661081","https://openalex.org/W4205496867","https://openalex.org/W6693109660"],"related_works":["https://openalex.org/W2017893921","https://openalex.org/W2082223167","https://openalex.org/W630244277","https://openalex.org/W1993632358","https://openalex.org/W2904925901","https://openalex.org/W2065471786","https://openalex.org/W2393573774","https://openalex.org/W1988705673","https://openalex.org/W1586969640","https://openalex.org/W2084517856"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"study":[2,77],"has":[3],"proposed":[4,78,127,183],"a":[5,10,39,79,143,194],"method":[6,80,128,137,184],"for":[7,34,81,163,173],"detecting":[8,35],"turbulence,":[9],"primary":[11],"factor":[12],"that":[13],"influences":[14],"safe":[15],"aircraft":[16],"operation.":[17],"The":[18],"number":[19,41],"of":[20,30,42,50,64,146,200],"observed":[21],"turbulence":[22,36,65,83,88,123,147,164,175,202],"events":[23,37],"is":[24],"limited,":[25],"thereby":[26],"indicating":[27],"the":[28,46,56,61,87,122,126,135,155,167,178,182,198,201],"requirement":[29],"an":[31],"appropriate":[32],"flow":[33],"from":[38,102],"small":[40],"samples.":[43],"In":[44],"addition,":[45],"opinions":[47],"and":[48,149],"experiences":[49],"pilots":[51],"must":[52],"be":[53],"reflected":[54],"at":[55],"initial":[57],"stage":[58],"to":[59,120,138,196],"address":[60],"high":[62,144],"risk":[63,140,156],"occurrence,":[66,165],"which":[67],"can":[68],"result":[69],"in":[70,106],"airline":[71],"operations":[72],"being":[73],"cancelled.":[74],"Thus,":[75],"this":[76],"predicting":[82,174],"occurrence":[84,89,124,148,203],"based":[85],"on":[86],"date":[90,204],"information":[91],"provided":[92],"by":[93,193],"airlines":[94],"as":[95,97,108,160,188,190],"well":[96,189],"meteorological":[98],"data":[99,104,162],"sets":[100],"obtained":[101,180],"open":[103],"available":[105],"Japan":[107],"teacher":[109],"data.":[110],"However,":[111],"because":[112],"commonly":[113],"used":[114,172],"machine":[115,170],"learning":[116],"methods":[117],"are":[118],"unable":[119],"detect":[121],"date,":[125],"employed":[129],"principal":[130],"component":[131],"analysis":[132],"coupled":[133],"with":[134,142,181],"K-Means":[136],"generate":[139],"clusters":[141,157],"likelihood":[145],"consequently":[150],"perform":[151],"statistical":[152],"checks.":[153],"Subsequently,":[154],"were":[158,185],"utilized":[159],"supervisory":[161],"while":[166],"support":[168],"vector":[169],"was":[171],"occurrence.":[176],"Furthermore,":[177],"results":[179],"statistically":[186],"checked":[187],"practically":[191],"verified":[192],"pilot":[195],"confirm":[197],"appropriateness":[199],"predicted.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2025-10-10T00:00:00"}
