Abstract
In order to solve the problems of poor regional control effect and high control difficulty coefficient of a traditional tourism flow, this paper puts forward the research of a regional control of tourism flow based on fuzzy theory. The capacity of regional tourism is determined by analyzing the factors that influence the regional control of the tourism flow. The regional tourism flow is divided into different time series by automatic clustering algorithm, the same sample data is fused, and the Euclidean distance between traffic is obtained. The regional tourism flow prediction model is constructed according to fuzzy theory. On this basis, the real-time capacity of regional scenic spot flow is calculated, and the regional tourist flow control model is constructed to realize the regional tourist capacity control. The experimental results show that the regional control error of tourism flow is always lower than 0.40, and the difficulty coefficient of control is low, which has certain advantages.
Highlights
Global tourism has developed rapidly in recent years
(2) The regional tourism traffic is divided into different time series by automatic clustering algorithm, the same sample data is fused, and the Euclidean distance between traffic is obtained, and the regional tourism traffic prediction model is constructed according to fuzzy theory
The regional tourism flow is divided into different time series by automatic clustering algorithm, the same sample data is fused, and the Euclidean distance between traffic is obtained
Summary
Global tourism has developed rapidly in recent years. More and more countries will speed up the development of tourism as a strategic decision, and our country will position tourism as a strategic pillar industry and modern service industry to cultivate it and issued the Tourism Law to ensure and promote the sustainable and healthy development of tourism [1]. Literature [7] puts forward the real-time tracking and prediction method of tourist flow data in scenic spots under cloud computing. The real-time tracking and prediction method of tourist flow data in scenic spots under cloud computing is put forward. (1) To determine the capacity of regional tourism by analyzing the factors affecting the regional control of tourism flows (2) The regional tourism traffic is divided into different time series by automatic clustering algorithm, the same sample data is fused, and the Euclidean distance between traffic is obtained, and the regional tourism traffic prediction model is constructed according to fuzzy theory (3) On this basis, the real-time traffic capacity of regional scenic spots is calculated, and the regional tourist flow control model is constructed to realize the regional tourist capacity control (4) Experimental analysis (5) Concluding remarks
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