• Login
  • Register
  • Search

Implementation and Application of Genetic Hybrid Neural Tourism Algorithm

Xiong Jiang, Jian Li


This paper calculates the value of tourism customers, collects and identifies the tourism interests of customers according to the estimated results, optimizes the processing method of customer interest samples based on hybrid neural genetic algorithm, and improves the steps of tourism customer loss prediction. The results show that the prediction method of tourism customer turnover based on the mixed neural genetic algorithm improves the prediction accuracy of customer turnover.


Tourist Customers; Prediction of Customer Turnover

Full Text:


Included Database


Guliyev H, Tatoğlu FY. 2021, Customer churn analysis in banking sector: Evidence from explainable machine learning models. Journal Of Applied Microeconometrics, 1(2): 85-99.

Mirkovic M, Lolic T, Stefanovic D, Anderla A, Gracanin D. 2022, Customer Churn Prediction in B2B Non-Contractual Business Settings Using Invoice Data. Applied Sciences, 12(10): 5001.

Maw M, Haw SC, Ho CK. 2021,Utilizing data sampling techniques on algorithmic fairness for customer churn prediction with data imbalance problems. F1000Research, 10(988): 988.

DOI: http://dx.doi.org/10.18686/fm.v8i5.9008