As the main infrastructure of the tourism industry, the hotel industry is an important part of the tourism industry and one of the important symbols of the development level of the tourism industry. In recent years, with the prosperity and development of the hotel industry, it can not only effectively solve many social work problems but also contribute to the further development of the region’s economy. In this paper, the convergence model and fitness function of the GSO-MCM algorithm are evaluated, and the optimal adaptive threshold of the particle swarm is given. The impact of computational intelligence on the development of hotel and tourism economy is analyzed, and the accuracy of computational intelligence method, data mining method, and fuzzy statistical method are evaluated and compared. The computational intelligence method shows better performance. The domestic tourism revenue is predicted using computational intelligence and compared with the actual value, which shows a good prediction effect. The hotel industry, an important tourism infrastructure, is an important symbol of the level of development of the tourism industry. In recent years, the rise of the hotel industry has not only effectively addressed many of the company’s labor problems but also made great contributions to the region's economic growth. With this in mind, we are conducting pilot studies on data collection.

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