<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Eco-agricultural characteristic tourism is one of the important contents of China’s tourism research, and is also one of the important initiatives to solve the “three rural problems” and realize comprehensive well-off. This paper proposes a particle algorithm-optimized RBF neural network model based on a neural network, which greatly overcomes the defects of its busy convergence speed and complex learning and calculation process. This paper uses this neural network to analyze and summarize the existing historical data on ecological and agricultural characteristics of tourism management, and presents the current problems of agricultural characteristics of tourism management to the tourist site managers in the form of data, to develop the ecological and agricultural characteristics of tourism management mechanism. The analysis of data focuses on passenger flow management, human resource structure management, and tourist satisfaction management in tourism management. The data calculation indicates that the staff at the scenic spot has an inadequate educational degree and lacks strong professionalism. In this regard, the eco-agricultural tourism attractions make corrective measures, the proportion of employees with a bachelor’s degree and above is pulled to 39%, and the average value of tourists’ experience of the attraction reaches 0.737. The neural network model proposed in this paper can effectively analyze and summarize the data of the characteristic tourism management, and provide data support for the improvement and development of the eco-agricultural characteristics of the management of tourism.</p>
</abstract>

Eco-agricultural characteristic tourism is one of the important contents of China’s tourism research, and is also one of the important initiatives to solve the “three rural problems” and realize comprehensive well-off. This paper proposes a particle algorithm-optimized RBF neural network model based on a neural network, which greatly overcomes the defects of its busy convergence speed and complex learning and calculation process. This paper uses this neural network to analyze and summarize the existing historical data on ecological and agricultural characteristics of tourism management, and presents the current problems of agricultural characteristics of tourism management to the tourist site managers in the form of data, to develop the ecological and agricultural characteristics of tourism management mechanism. The analysis of data focuses on passenger flow management, human resource structure management, and tourist satisfaction management in tourism management. The data calculation indicates that the staff at the scenic spot has an inadequate educational degree and lacks strong professionalism. In this regard, the eco-agricultural tourism attractions make corrective measures, the proportion of employees with a bachelor’s degree and above is pulled to 39%, and the average value of tourists’ experience of the attraction reaches 0.737. The neural network model proposed in this paper can effectively analyze and summarize the data of the characteristic tourism management, and provide data support for the improvement and development of the eco-agricultural characteristics of the management of tourism.

Research on the Management of Ecological Agricultural Characteristic Tourism Development Based on Artificial Intelligence Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Eco-agricultural characteristic tourism is one of the important contents of China’s tourism research, and is also one of the important initiatives to solve the...

Research on the Management of Ecological Agricultural Characteristic Tourism Development Based on Artificial Intelligence Technology

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 26. Dez. 2023

Akzeptiert: 31. Dez. 2023

DOI: https://doi.org/10.2478/amns-2024-0306

Schlüsselwörter
Particle swarm algorithm, RBF neural network, Ecological agriculture, Tourism management

© 2024 Zhide Luo, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Management of Ecological Agricultural Characteristic Tourism Development Based on Artificial Intelligence Technology

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 26. Dez. 2023

Akzeptiert: 31. Dez. 2023

DOI: https://doi.org/10.2478/amns-2024-0306

SchlüsselwörterParticle swarm algorithm, RBF neural network, Ecological agriculture, Tourism management

© 2024 Zhide Luo, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Particle swarm algorithm, RBF neural network, Ecological agriculture, Tourism management