Application of Artificial Intelligence-Based Sensor Technology in the Recommendation Model of Cultural Tourism Resources

Abstract

Aiming at the lack of theoretical basis for the development of cultural tourism resources, an application method of artificial intelligence-based sensor technology in the recommendation model of cultural tourism resources is proposed. Sensor network is an application-based network. Compared with traditional wireless communication network, it has the characteristics of large node scale, self-organized multihop, unattended, and no communication infrastructure. Combined with artificial intelligence sensor technology, this paper attempts to construct an evaluation index system and evaluation model for cultural tourism resources, and uses this model to conduct a comprehensive evaluation of cultural ecotourism resources in the western region. The experimental results show that theEvalue of the evaluation result of cultural tourism resources in the western region is 6.346, which has a good development value. Secondly, from the specific evaluation results of each level, the western region has the highest cultural tourism standard, which has 6.605. Cultural tourism resources, landscape resources, and development conditions scored lower. Among them, cultural tourism resources and landscape resources have the highest score (7.186), and the economic and cultural field has the lowest score (6.092). Among the cultural tourism development conditions, the policy conditions are high (6.823), but the location conditions are very low, only 4.879 points. Therefore, it is found that the model takes cultural tourism landscape resources, cultural tourism environment resources, and cultural tourism development conditions as the content of cultural tourism resources evaluation, which is comprehensive and has strong hierarchy and pertinence; fuzzy comprehensive evaluation method has strong objectivity to determine the weight and the value classification; and weighting evaluation model of cultural tourism resources has rationality and generalizability and can provide a scientific basis for the classification and evaluation of cultural tourism resources and the planning and development of cultural tourism.