Predicting Hotel Performance in Oman with AI-Driven Predictive Analytic

被引:1
|
作者
Al Jassim, R. S. [1 ]
Jetly, Karan [1 ]
Al Mansoory, Shqran [1 ]
Al-Balushi, Muna [1 ]
Al Maqbali, Hilal [1 ]
机构
[1] Univ Technol & Appl Sci, Muscat, Oman
关键词
Genetic Programming; Decision Tree; Tourism; CUSTOMER;
D O I
10.1007/978-3-031-34107-6_38
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The primary objective of this study is to assess the performance of hotels in Oman by developing an AI based model using a new approach that we refer to as Linear Genetic Programming for Optimization Decision Tree (LGPDT). The LGPDT algorithm seeks to optimize decision trees, automatically select relevant input attributes, and adjust hyperparameters to improve prediction accuracy. The research findings demonstrate promise after testing the model with datasets from literature and the tourism sector. This approach has the potential to improve the assessment of hotel performance in Oman by providing accurate predictions of customer satisfaction, empowering managers to enhance their services and meet customers' demands more effectively.
引用
收藏
页码:478 / 490
页数:13
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