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Comparison of machine learning algorithms to predict optimal dwelling time for package tour
  • Aria Wahyutama,
  • Mintae Hwang
Aria Wahyutama
Changwon National University College of Engineering

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Mintae Hwang
Changwon National University College of Engineering
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This paper shows the comparison between several well-known classification algorithms in Machine Learning with the purpose to find the most suitable algorithm to predict the dwelling time i.e., how long a certain tourist should stay in a particular tourist spot. This dwelling time prediction can be adopted for tour and travel agents to provide optimal scheduling for their package tour. The algorithm in question is strictly for classification because in this case, the dwelling time does not require a very specific number of minutes, thus the time can be classified and restricted into several time frames. The origin and features of the dataset are described in this paper as well as the comparison methodology to show the procedure of how the comparison was made. Lastly, the performance results will be used to determine which algorithm to use for this specific case and it will be shown in a form of a graph
20 Jul 2022Submitted to Electronics Letters
20 Jul 2022Submission Checks Completed
20 Jul 2022Assigned to Editor
22 Jul 2022Reviewer(s) Assigned
22 Sep 2022Review(s) Completed, Editorial Evaluation Pending
22 Sep 2022Editorial Decision: Revise Minor
03 Oct 20221st Revision Received
04 Oct 2022Submission Checks Completed
04 Oct 2022Assigned to Editor
04 Oct 2022Review(s) Completed, Editorial Evaluation Pending
06 Oct 2022Editorial Decision: Accept
Nov 2022Published in Electronics Letters volume 58 issue 24 on pages 902-904. 10.1049/ell2.12651