Market segmentation and demand forecasting of international tourism service trade based on CNN DOI Creative Commons
Wenhao Wang

Published: March 13, 2025

In the context of globalization and informatization, international tourism service trade has become an important part global economy. As changes in demand are affected by multiple factors such as economic situation, policy adjustments, consumer behavior, traditional forecasting methods have been unable to cope with complex market changes. Based on convolutional neural network (CNN) model, this study segmented forecasted market. Through multi-dimensional data, model can automatically extract features from effectively identify potential laws changes, provide accurate forecasts. Experimental results show that CNN high accuracy predicting macro trends major markets. However, certain errors dealing short-term fluctuations markets slow recovery. To end, future research optimize combining other deep learning models improve prediction computational efficiency model. The provides a scientific basis for decision-making industry promotes sustainable development industry.

Language: Английский

Market segmentation and demand forecasting of international tourism service trade based on CNN DOI Creative Commons
Wenhao Wang

Published: March 13, 2025

In the context of globalization and informatization, international tourism service trade has become an important part global economy. As changes in demand are affected by multiple factors such as economic situation, policy adjustments, consumer behavior, traditional forecasting methods have been unable to cope with complex market changes. Based on convolutional neural network (CNN) model, this study segmented forecasted market. Through multi-dimensional data, model can automatically extract features from effectively identify potential laws changes, provide accurate forecasts. Experimental results show that CNN high accuracy predicting macro trends major markets. However, certain errors dealing short-term fluctuations markets slow recovery. To end, future research optimize combining other deep learning models improve prediction computational efficiency model. The provides a scientific basis for decision-making industry promotes sustainable development industry.

Language: Английский

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