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开发基于人工智能的餐厅菜单需求预测模型,利用销售和气象数据进行预测
1Department of Food Engineering, Dankook University, 119, Dandae-ro, Dongnam-gu, Cheonan, Chungcheongnam-do 31116 Republic of Korea.
Food science and biotechnology
|October 20, 2025
概括
这项研究引入了一个人工智能系统来预测餐厅的每日销售额,这对于减少食物浪费和提高效率至关重要. 该系统使用历史数据和天气信息来预测单个菜单项的需求.
科学领域:
- 人工智能的人工智能
- 运营研究 运营研究
- 数据科学数据科学数据科学
背景情况:
- 准确的需求预测对于餐厅的运营效率至关重要.
- 关键的挑战包括库存管理和减少食物浪费.
研究的目的:
- 开发一种基于人工智能的系统,用于预测特定菜单的每日销售额.
- 通过数据驱动的洞察力提高餐厅的运营效率和可持续性.
主要方法:
- 利用历史销售和气象数据 (2021-2023).
- 开发了深度神经网络,用于对384个菜单项目进行多类分类.
- 实现了用于销售预测分析的灵活可视化.
主要成果:
- 实现了高预测性能,平均皮尔森相关系数为0.7945.5.
- 证明了系统能够预测单个菜单项的销售额的能力.
- 展示了销售数据的实用可视化工具.
结论:
- 人工智能驱动的需求预测对餐饮行业来说是可行的和有效的.
- 该系统有可能改变食品服务业务.
- 突出了提高食品服务的可持续性和效率的途径.
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