用混合模型预测中国宠物数量，揭示收入与政策是关键驱动力
Driving Mechanisms and Forecasting of China's Pet Population-An ARIMA-RF-HW Hybrid Approach
- 融合ARIMA、随机森林和霍尔特-温特斯模型，捕捉趋势、非线性和季节性
- 城市收入和政策数量对猫狗数量影响最大，猫增长稳定，狗波动明显
- 适合政策制定者和宠物行业企业参考，助力精准服务与可持续发展
本研究提出一种动态加权的ARIMA-RF-HW混合模型，整合ARIMA捕捉趋势与季节性、随机森林处理非线性特征、霍尔特-温特斯进行季节调整，以提升中国宠物数量预测精度。基于2005-2023年数据，结合九项经济、社会与政策指标（如城镇居民收入、消费水平、老龄化率、政策数量、新兽药批准数），通过Z-score标准化与缺失值填补完成数据预处理。结果表明，城市收入（猫19.48%、狗17.15%）、消费水平（猫17.99%）、政策数量（猫13.33%、狗14.02%）为关键驱动因素，老龄化（猫12.81%、狗13.27%）及城市化进一步放大宠物需求。预测显示猫群持续增长，狗群则呈现波动特征，反映猫更适应城市环境。研究成果可支持政策优化宠物健康管理，指导企业差异化服务设计，推动产业可持续发展。
原文摘要 · Abstract (English)
This study proposes a dynamically weighted ARIMA-RF-HW hybrid model integrating ARIMA for seasonality and trends, Random Forest for nonlinear features, and Holt-Winters smoothing for seasonal adjustment to improve China's pet population forecasting accuracy. Using 2005-2023 data with nine economic, social, and policy indicators (urban income, consumption, aging ratio, policy quantity, new veterinary drug approvals), data were preprocessed via Z-score normalization and missing value imputation. The results show that key drivers of pet populations include urban income (19.48% for cats, 17.15% for dogs), consumption (17.99% for cats), and policy quantity (13.33% for cats, 14.02% for dogs), with aging (12.81% for cats, 13.27% for dogs) and urbanization amplifying the demand for pets. Forecasts show steady cat growth and fluctuating dog numbers, reflecting cats' adaptability to urban environments. This research supports policymakers in optimizing pet health management and guides enterprises in developing differentiated services, advancing sustainable industry growth.
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