An Empirical Study on Intelligent Rural Tourism Service by Neural Network Algorithm Models

Jingzhi Chen,Sang-Bing Tsa,Hongbo Xue,Zaoli Yang

doi:10.1155/2021/4156904

Abstract

With the continuous development of social economy, tourism has become one of the many choices and is becoming more and more popular. However, it should be noted that how to provide high-quality and efficient tourism services is extremely important. This paper introduces the neural network algorithm and the optimal classification decision function, through unified combing, classification, and coding of scenic spots, to achieve the subclass classification of scenic spots, based on the optimal distribution function of random intelligent selection, and the formation of the corresponding scenic spots traversal clear tourism routes. The corresponding motivation iteration is obtained by using the corresponding travel route transmission, the best travel route is defined, the corresponding auxiliary decision support is provided, and the simulation experiment is carried out. The experimental results show that the neural network algorithm and the optimal classification decision function are effective and can support the intelligent decision assistance of rural tourism service.

Highlights

With the continuous development of social economy, tourism has become a more and more popular choice, especially in holidays as one of the important activities of many people [1]
Due to the weak infrastructure, rural tourism is deficient in food, accommodation, and other aspects to a certain extent, which needs further improvement [4, 5]. If they have a high evaluation of the whole place, they will have a high willingness to travel. ese factors are easy to exist in the bus routes and road congestion of scenic spots, causing the interference of tourism activities [6, 7]. erefore, how to determine the best route according to the corresponding factors between scenic spots, maximize the benefits of tourism, and save the corresponding cost, for the provision of corresponding services is extremely important
How to promote rural tourism, on the one hand, ensures normal and healthy development, and on the other hand, harmoniously coexists with the natural environment [9, 11, 12]. erefore, in view of these situations, this paper introduced the neural network algorithm and the optimal classification decision function, and through the study of the topology relation network construction of rural scenic spots, tourist attractions are formed by random choice; according to the corresponding iterative interference factors analysis, the quantitative analysis of different tours as a decision aid to support the reasonable route and sorting and the choice of maximum as the best route aim to promote rural tourism and develop the local economy

Summary

Introduction

With the continuous development of social economy, tourism has become a more and more popular choice, especially in holidays as one of the important activities of many people [1]. Due to the weak infrastructure, rural tourism is deficient in food, accommodation, and other aspects to a certain extent, which needs further improvement [4, 5] If they have a high evaluation of the whole place, they will have a high willingness to travel. Erefore, in view of these situations, this paper introduced the neural network algorithm and the optimal classification decision function, and through the study of the topology relation network construction of rural scenic spots, tourist attractions are formed by random choice; according to the corresponding iterative interference factors analysis, the quantitative analysis of different tours as a decision aid to support the reasonable route and sorting and the choice of maximum as the best route aim to promote rural tourism and develop the local economy How to promote rural tourism, on the one hand, ensures normal and healthy development, and on the other hand, harmoniously coexists with the natural environment [9, 11, 12]. erefore, in view of these situations, this paper introduced the neural network algorithm and the optimal classification decision function, and through the study of the topology relation network construction of rural scenic spots, tourist attractions are formed by random choice; according to the corresponding iterative interference factors analysis, the quantitative analysis of different tours as a decision aid to support the reasonable route and sorting and the choice of maximum as the best route aim to promote rural tourism and develop the local economy

Neural Network Algorithm and Optimal Classification Decision Function

Algorithm Design

Intelligent Construction Path of Rural Tourism Service

Conclusions