Integrating a Neural Network Model based on LSTM and Auto Encoder into the Travel and Tourism Industry

The travel and tourism sector is one of the world’s most important economic drivers. This study analyzes the growth and transformation of the worldwide tourism sector. What keeps the economy going, what generates employment, what contributes to social stability, and what drives societal development. The industry is crucial to the global economy, supporting the livelihoods of hundreds of millions of people. When it comes to economic activity, tourism often serves as the only game in town on many islands. The ultimate goal of the role is to encourage the development of sustainable economies. From the greatest global travel companies to the smallest tour operators or hostel proprietors, the travel and tourism business employs millions of people worldwide. It can achieve real changes in the political and social systems through our work together. Preprocessing, feature selection, and model training are the three main components of the proposed method. Preprocessing is performed to clean the data. The model’s efficacy is measured using LSTM-AE after undergoing a filter-based and recursive feature selection process.