Enhancing Hotel Performance Prediction in Oman's Tourism Industry: Insights from Machine Learning, Feature Analysis, and Predictive Factors
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gp-bibliography.bib Revision:1.8344
- @InProceedings{Al-Jassim:2024:EAIS,
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author = "Rasha S. {Al Jassim} and Shqran {Al Mansoory} and
Karan Jetly and Hilal AlMaqbali",
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title = "Enhancing Hotel Performance Prediction in Oman's
Tourism Industry: Insights from Machine Learning,
Feature Analysis, and Predictive Factors",
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booktitle = "2024 IEEE International Conference on Evolving and
Adaptive Intelligent Systems (EAIS)",
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year = "2024",
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month = may,
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keywords = "genetic algorithms, genetic programming, Accuracy,
Machine learning algorithms, Tourism industry,
Stability criteria, Prediction algorithms, Robustness,
Decision trees, Decision Tree, Evolutionary Algorithms,
XG-Boost",
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ISSN = "2473-4691",
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DOI = "
doi:10.1109/EAIS58494.2024.10570014",
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abstract = "This paper introduces two novel fitness functions
adapted to attraction attributes, extending the
capabilities of the Linear Genetic Programming for
Optimisation Decision Tree (LGPDT). A comparative
analysis with XGBoost evaluates LGPDT's performance
using both traditional and tourism datasets, examining
its predictive capacity for hotel performance in Oman.
Using extensive experiments and analysis, the study
proved the effectiveness of LGPDT in this context,
revealing promising results with a mean accuracy of
72.0percent and a standard deviation of 7.7percent.
This underscores LGPDT's robustness and suitability for
decision-making in the hospitality industry. Comparison
with XGBoost demonstrates LGPDT's slightly higher
stability in accuracy, highlighting its potential as a
predictive tool. Moreover, the evaluation of new
fitness functions reveals that they are computationally
efficient while maintaining similar quality standards
compared to previously studied fitness functions. These
findings underscore LGPDT's efficacy for predicting
hotel performance, offering valuable insights for
industry stakeholders.",
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notes = "Also known as \cite{10570014}",
- }
Genetic Programming entries for
Rasha S Al Jassim
Shqran Al mansoory
Karan Jetly
Hilal Al-maqbali
Citations