Implementation of a Tourist Route Neural Network Using Data Augmentation for Personalized Travel Insights

Abstract

This research aims to develop and implement a neural network model for optimizing tourist route planning, based on data sourced from tourism agencies in Azerbaijan for the year 2025. Due to limited available data, this study utilizes web scraping techniques for data collection and applies statistical methods such as normal distribution and Monte Carlo simulations to augment the dataset. Hypothesis testing is performed to analyze correlations between demographic factors, such as age groups, and preferences for specific tourist destinations. The objective of this research is to generate personalized travel recommendations that cater to individual interests and to provide insights into optimizing the tourist experience for the broader tourism sector