ASSESMENT OF TICKET PRICE FORECASTING IN TURKEY

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dc.contributor.authorDosdoğru, Ayşe Tuğba
dc.contributor.authorİpek, Aslı Boru
dc.contributor.authorGöçken, Mustafa
dc.contributor.authorÖzçalıcı, Mehmet
dc.date.accessioned2025-01-06T17:23:24Z
dc.date.available2025-01-06T17:23:24Z
dc.date.issued2022
dc.departmentAdana Alparslan Türkeş Bilim ve Teknoloji Üniversitesi
dc.description.abstractFast, reliable and comfortable transportation of people increases the level of livability in cities. It also influences people's quality of life. Therefore, researches are needed to improve transportation services. Various models are developed to analyze the transportation services but each of which has its own advantages and disadvantages. Today, companies collect large amounts of data to improve their service quality. To survive in competition environment, they must use the collected data in order to create value for their customers and employees. There are many factors that affect the transportation services. Therefore, it is difficult to solve the problems in transportation services using classical methods. The main goal of our study is to determine the bus ticket price accurately. In this study, k-means algorithm, which is popular because of its simplicity and versatility, is firstly used to discover more meaningful information. Then the price, which is one of the most important elements of passenger transportation, is forecasted using six different forecasting model including linear regression, support vector regression, regression tree, gaussian process regression, genetic algorithm based artificial neural network, and ensemble model. The results of this study showed that proposed forecasting models can meet expectations in dynamic environmental conditions.
dc.identifier.doi10.35379/cusosbil.1030398
dc.identifier.endpage144
dc.identifier.issn1304-8880
dc.identifier.issn1304-8899
dc.identifier.issue1
dc.identifier.startpage133
dc.identifier.trdizinid1105159
dc.identifier.urihttps://doi.org/10.35379/cusosbil.1030398
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1105159
dc.identifier.urihttps://hdl.handle.net/20.500.14669/771
dc.identifier.volume31
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofÇukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectSupport vector regression
dc.subjectLinear regression
dc.subjectK-means algorithm
dc.subjectGenetic algorithm based artificial neural network
dc.subjectTicket price forecasting
dc.titleASSESMENT OF TICKET PRICE FORECASTING IN TURKEY
dc.typeArticle

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