{"id":"https://openalex.org/W1582961025","doi":null,"title":"Comparison of linear regression and neural network models forecasting tourist arrivalsto Turkey","display_name":"Comparison of linear regression and neural network models forecasting tourist arrivalsto Turkey","publication_year":2012,"publication_date":"2012-05-31","ids":{"openalex":"https://openalex.org/W1582961025","mag":"1582961025"},"language":"en","primary_location":{"id":"mag:1582961025","doi":null,"is_oa":false,"landing_page_url":"https://eprints.ibu.edu.ba/1179/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5030737899","display_name":"Selcuk Cankurt","orcid":"https://orcid.org/0000-0003-0581-1913","observed_orcids":["https://orcid.org/0000-0003-0581-1913"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Selcuk Cankurt","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5076009908","display_name":"Abd\u00fclhamit Suba\u015f\u0131","orcid":"https://orcid.org/0000-0001-7630-4084","observed_orcids":["https://orcid.org/0000-0001-7630-4084"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abd\u00fclhamit Suba\u015f\u0131","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-7630-4084","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9980000257492065,"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"}},{"id":"https://openalex.org/T10055","display_name":"Diverse Aspects of Tourism Research","score":0.0006000000284984708,"subfield":{"id":"https://openalex.org/subfields/1409","display_name":"Tourism, Leisure and Hospitality Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.00019999999494757503,"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/tourist-arrivals-forecasting","display_name":"tourist arrivals forecasting","score":0.8289999961853027},{"id":"https://openalex.org/keywords/tourism-demand-modeling","display_name":"tourism demand modeling","score":0.9509999752044678},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":0.8889999985694885},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.9240000247955322},{"id":"https://openalex.org/keywords/multivariate-time-series-forecasting","display_name":"multivariate time series forecasting","score":0.777999997138977},{"id":"https://openalex.org/keywords/sustainable-tourism-development","display_name":"sustainable tourism development","score":0.9449999928474426},{"id":"https://openalex.org/keywords/turkey-tourism","display_name":"Turkey tourism","score":0.6039999723434448},{"id":"https://openalex.org/keywords/forecasting-model-comparison","display_name":"forecasting model comparison","score":0.5429999828338623}],"concepts":[{"id":"https://openalex.org/C18918823","wikidata":"https://www.wikidata.org/wiki/Q49389","display_name":"Tourism","level":2,"score":0.869762659072876},{"id":"https://openalex.org/C552854447","wikidata":"https://www.wikidata.org/wiki/Q131201","display_name":"Sustainable development","level":2,"score":0.6438695788383484},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6138882040977478},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.6014561653137207},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5860872864723206},{"id":"https://openalex.org/C2778734068","wikidata":"https://www.wikidata.org/wiki/Q1344240","display_name":"Sustainable tourism","level":3,"score":0.5499146580696106},{"id":"https://openalex.org/C64946054","wikidata":"https://www.wikidata.org/wiki/Q4874476","display_name":"Bayesian multivariate linear regression","level":3,"score":0.5434485077857971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5359547734260559},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5297708511352539},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4746573269367218},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.45410358905792236},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.44516533613204956},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.43231427669525146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34768396615982056},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3073890805244446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2875913977622986},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.28158289194107056},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.22919553518295288},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21729743480682373},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.08355611562728882},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:1582961025","doi":null,"is_oa":false,"landing_page_url":"https://eprints.ibu.edu.ba/1179/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7018206603","https://openalex.org/W4211148136","https://openalex.org/W2100115021","https://openalex.org/W3154986848","https://openalex.org/W1526127635","https://openalex.org/W2770196349","https://openalex.org/W160081930","https://openalex.org/W4366695659","https://openalex.org/W2469049207","https://openalex.org/W3110063645"],"abstract_inverted_index":{"This":[0],"paper":[1],"develops":[2],"statistical":[3],"and":[4,30,67,93,120],"machine":[5],"learning":[6],"methods":[7],"for":[8,17,57,105,130],"estimating":[9],"tourist":[10,86],"arrivals\r\nwhich":[11],"is":[12,37,70,83],"one":[13,25,38,78],"of":[14,26,39,44,64,79,108,113],"the":[15,19,27,40,45,58,65,74,80],"donnee":[16],"planning":[18,66],"sustainable":[20,46,59],"tourism":[21,35,49,54,60,69,149],"development.":[22,61],"Tourism":[23,136,138],"is\r\narguably":[24],"world's":[28],"largest":[29],"fastest":[31],"growing":[32],"industries.":[33],"Sustainable":[34],"development":[36],"most":[41],"promising":[42],"generators":[43],"economic\r\ndevelopment.":[47],"Realistic":[48],"projections":[50],"based":[51],"on":[52],"accurate":[53],"forecasting":[55,85,109],"contribute\r\nmuch":[56],"The":[62],"challenge":[63],"developing\r\nsustainable":[68],"to":[71,101],"see":[72],"as":[73],"complex":[75],"paradigm":[76],"but":[77],"starting":[81],"points":[82],"the\r\naccurate":[84],"arrivals.":[87],"In":[88],"this":[89],"study,":[90],"linear":[91],"regression":[92,131],"neural":[94],"network\r\nmultilayer":[95],"perceptron":[96],"(MLP)":[97],"implementations":[98],"are":[99],"considered":[100],"make":[102],"multivariate":[103],"tourism\r\nforecasting":[104],"Turkey.":[106],"Comparison":[107],"performances":[110],"in":[111],"terms":[112],"correlation\r\ncoefficient":[114],"(R),":[115],"relative":[116,122],"absolute":[117],"error":[118,124],"(RAE)":[119],"root":[121],"squared":[123],"(RRSE)\r\nmeasurements":[125],"shows":[126],"that":[127],"MLP":[128],"model":[129],"gives":[132],"a":[133],"better":[134],"performance.\r\nKeywords:":[135],"forecasting;":[137],"demand":[139],"modelling;":[140],"Time":[141],"series;":[142],"Linear":[143],"regression;\r\nNeural":[144],"networks;":[145],"Multilayer":[146],"perceptron;":[147],"Multivariate":[148],"forecasting.":[150]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-09-21T07:43:02.447757","created_date":"2016-06-24T00:00:00"}