V. Krylov, A. Sachenko, Pavlo Strubytskyi, Dmytro Lendiuk, H. Lipyanina, D. Zahorodnia, Vitaliy Dorosh, T. Lendyuk
{"title":"Multiple Regression Method for Analyzing the Tourist Demand Considering the Influence Factors","authors":"V. Krylov, A. Sachenko, Pavlo Strubytskyi, Dmytro Lendiuk, H. Lipyanina, D. Zahorodnia, Vitaliy Dorosh, T. Lendyuk","doi":"10.1109/IDAACS.2019.8924461","DOIUrl":null,"url":null,"abstract":"The object of the study is the automation process for tourist demand modeling, the characteristic feature of which is consideration of the most important factors. Demand is one of these factors, which stimulates the development of tourism. Information technology for tourist demand modeling with characteristics consideration of the most important factors is developed using the programming language R and a package Shiny.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAACS.2019.8924461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The object of the study is the automation process for tourist demand modeling, the characteristic feature of which is consideration of the most important factors. Demand is one of these factors, which stimulates the development of tourism. Information technology for tourist demand modeling with characteristics consideration of the most important factors is developed using the programming language R and a package Shiny.