Demand Prediction of Convention and Exhibition Tourism Based on Neural Networks

With the booming development of the exhibition and tourism industry, accurate demand forecasting is crucial for decision-making by relevant enterprises and management departments. This article delves into the prediction method of exhibition tourism demand based on neural network algorithms. Firstly, a systematic review was conducted on the relevant theories and research status of exhibition tourism both domestically and internationally. Secondly, the basic principles of neural network algorithms and their advantages in demand forecasting were elaborated in detail. Then, a neural network model suitable for predicting the demand for exhibition tourism was constructed, and appropriate sample data was selected for model training and validation. And through comparative analysis with traditional prediction methods, the superiority of this method in prediction accuracy and adaptability was verified; Finally, in-depth analysis and discussion of the predicted results will provide valuable reference for the development of the exhibition tourism industry.