Abstract: With the rise of self-drive travel, the market of China's recreational vehicle (RV) is showing a vigorous development. The purpose of this paper is to explore the main driving factors behind the sales market of RV, forecast and analyze the changing trend of the sales of RV. First of all, based on the relevant statistical data in the past ten years, through the Pearson correlation coefficient calculation, the main driving factors affecting the sales market of RV are per capita gross domestic product, per capita disposable income, highway miles and the number of people over 60 years old. Then, using the methods of time series analysis, multiple linear regression and neural network, it constructs the sales model of RVs, and forecast the sales volume of RVs in China in the next three years. The predicted sales volume is compared with the actual sales volume to determine the prediction accuracy of each model. The results show that the highest goodness of fit is the multiple linear regression model, which predicts the sales volume of China's passenger cars in 2024－2026 are 15 737, 17 215 and 18 693 respectively. The research results can provide an important basis for making production plan, adjusting market strategy and optimizing resource allocation.

Key words: recreational vehicle; sales forecast; time series; multiple linear regression; neural network

摘要： 随着自驾游的兴起，中国旅居车（RV）市场呈现出蓬勃发展的态势。文章旨在深入探 讨旅居车销售市场背后的主要驱动因素，预测和分析旅居车销量的变化趋势。首先基于近十 年来的相关统计数据，通过皮尔逊相关系数计算，得到影响旅居车销售市场的主要驱动因素 有国内人均生产总值、人均可支配收入、公路里程数以及 60 岁以上人口数量。随后，分别运 用时间序列分析、多元线性回归以及神经网络方法构建了旅居车的销量模型，对中国旅居车 未来三年的销量进行了预测，并将预测销量与实际销量进行比较，确定各模型的预测精度。 结果显示，拟合优度最高的是多元线性回归模型，其预测的 2024－2026 年中国旅居车销量分 别为 15 737、17 215、18 693 辆。研究结果可为旅居车行业企业制定生产计划、调整市场策 略、优化资源配置提供重要依据。

关键词: 旅居车；销量预测；时间序列；多元线性回归；神经网络