Abstract
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.
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Al Jassim, R.S., Jetly, K., Al Mansoory, S., Al-Balushi, M., Al Maqbali, H. (2023). Predicting Hotel Performance in Oman with AI-Driven Predictive Analytic. In: Maglogiannis, I., Iliadis, L., MacIntyre, J., Dominguez, M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2023. IFIP Advances in Information and Communication Technology, vol 676. Springer, Cham. https://doi.org/10.1007/978-3-031-34107-6_38
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DOI: https://doi.org/10.1007/978-3-031-34107-6_38
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