基于机器学习的良仓烘焙店销售需求预测模型研究

Research on the Sales Demand Prediction Model of Liangcang Bakery Based on Machine Learning

摘要: 随着消费者需求的波动性和市场竞争的加剧，烘焙行业对销售需求预测的精确度提出了更高的要求。传统的销售预测方法，如基于历史平均值或时间序列分析，无法有效应对烘焙店销售中复杂的季节性、促销活动以及其他多因素影响。为此，本文以良仓烘焙店为例，探讨了烘焙产品的销售特性及影响销售需求的因素，分析了传统预测方法的局限性。通过对机器学习算法的应用基础进行探讨，构建了以历史销售数据为基础的销售需求预测模型，以期为烘焙店优化经营策略提供参考。

Abstract: With the volatility of consumer demand and the intensification of market competition, the baking industry has put forward higher requirements for the accuracy of sales demand forecasting. Traditional sales forecasting methods, such as those based on historical averages or time series analysis, are unable to effectively address the complex seasonality, promotional activities, and other multi factor influences in bakery sales. Therefore, this article takes Liangcang Bakery as an example to explore the sales characteristics of baked goods and the factors that affect sales demand, and analyzes the limitations of traditional forecasting methods. By exploring the application foundation of machine learning algorithms, a sales demand forecasting model based on historical sales data was constructed to provide reference for optimizing business strategies in bakeries.