Establishment of Genetic Hybrid Neurotourism Algorithm
Xiong Jiang
Jian Li
DOI: https://doi.org/10.59429/esta.v10i5.1402
Keywords: Mixed Neurogenetics; Tourist Customers; Customer
Abstract
In order to grasp the changing trend of customer churn and improve the prediction accuracy of customer churn, a prediction method of tourism customer churn based on Hybrid Neural Genetics is proposed. The mixed neural genetic algorithm is used to model and predict the customer turnover, estimate the tourism customer value calculation.
References
Lian J, Fang SY, Zhou YU. 2020, Model Predictive Control of the Fuel Cell Cathode System Based on State Quantity Estimation.Computer Simulation, 37(07): 119-122.
Lalwani P, Mishra MK, Chadha JS, Sethi P. 2022, Customer churn prediction system: a machine learning approach. Computing, 104(2): 271-294.
Pustokhina IV, Pustokhin DA, Aswathy RH, Jayasankar T, Jeyalakshmi C, Díaz C, V, Shankar K. 2021, Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms. Information Processing & Management, 58(6): 102706.