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English(EN) A Machine Learning Framework for Predicting Restaurant Food Waste to Support Sustainable Food Management

机器学习框架预测餐厅食物浪费

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一个机器学习框架，利用运营数据、天气和活动指标来估算餐厅的每日食物浪费。该研究构建了一个包含77,980条记录的数据集，并采用了四种回归模型，其中随机森林表现最佳。确定的关键预测因素包括菜单多样性、运营区域和时间活动模式。数据集、代码和实验配置均公开可用，以鼓励进一步研究，特别是使用实测浪费数据进行的研究。 AI

影响 通过数据驱动的洞察，为餐厅提供减少浪费和提高可持续性的框架。

排序理由 详细介绍新机器学习框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

机器学习框架预测餐厅食物浪费

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详细介绍新机器学习框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Md Mehedi Hasan Naeem, Md Ashraful Islam, Moumita Barua, Ishtiyak Ahmmad Araf, Md. Arefin Haque Mahir ·

    用于预测餐厅食物浪费以支持可持续食品管理的机器学习框架

    arXiv:2609.08078v1 Announce Type: new Abstract: Food waste in the restaurant sector poses a substantial challenge to environmental sustainability and economic efficiency. This paper presents an exploratory machine learning framework for estimating daily restaurant food waste quan…

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