Research on the Number of Tourists Prediction Based on Genetic Algorithm Optimization Grey Neural Network

Abstract

该文以旅游人数为研究对象，初步选取影响旅游人数的13个因素，首先建立基于遗传算法优化灰色神经网络模型对旅游人数进行预测。为了进一步提高模型预测精度，采用灰色关联度法和平均值影响法两种方法对影响因素进行变量筛选，选取影响程度大的因素代入模型进行预测。分析比较模型的结果，可得经过平均值影响法变量筛选后的模型预测精度最高，误差最小。 Taking the number of tourists as the research object, this paper preliminarily selects 13 factors that affect the number of tourists, and firstly establishes a grey netural network model based on genetic algorithm to predict the number of tourists. In order to improve the prediction accuracy of the model, grey correlation degree method and average influence method were used to screen the variables of factors, and the factors with high influence degree were selected and substituted into the model for prediction. By analyzing and comparing the results of the model, it can be concluded that the model with the influence of the average value has the highest prediction accuracy and minimum error after selecting the normal variables.