食堂就餐人数预测数据

食堂就餐人数预测数据是一个对食堂运营至关重要的工具，它可以帮助与食堂有关的各相关方进行更有效的规划和管理。1.通过预测数据，食堂可以更准确地规划并准备未来一周的食材和物资库存，避免过剩或短缺，减少浪费。2.对于供应商来说，以本数据为基础，可以进一步推算食材和物资的合理供应量，优化配送计划，减少因供需不匹配导致成本的增加。3.本数据还能给有意入驻食堂的店铺或想借助食堂场地进行促销的商家提供参考，为制定营销或促销策略提供决策支持。1.数据抽取和预处理：
（1）数据抽取：在自研的5G智慧食安工业物联网数字化管理平台数据库中抽取相关食堂的每日用筷数量，包括日期、食堂编号、所在地区、今日用筷数量。（2）数据预处理：对抽取的数据进行清洗，去除重复、错误或无关的信息，以便后续的分析和建模。
2.基于用筷数量预测食堂未来就餐人数：
（1）计算本期和上期平均用筷数量：利用SUM函数分别对本期（含今日的近7天）和上期（近8-14天）的用筷数量进行累加；本期（含今日的近7天）平均用筷数量=本期累加数量÷7；上期（近8-14天）平均用筷数量=上期累加数量÷7。
（2）计算本期较上期平均用筷数量变化率和近三期平均变化率：本期较上期平均用筷数量变化率=（本期平均用筷数量-上期平均用筷数量）÷本期平均用筷数量×100%；近三期平均变化率=前三期平均用筷数量变化率之和÷3。
（3）建立下期就餐人数预测模型：下期（未来7天）预测平均用筷数量=本期平均用筷数量×（1+近三期平均变化率）；下期（未来7天）预测就餐人数=下期（未来7天）预测平均用筷数量×7。

Canteen dining patronage prediction data is an essential tool critical to canteen operations, enabling all relevant stakeholders associated with canteen management to carry out more effective planning and management.
1. Through the prediction data, canteens can more accurately plan and prepare ingredients and material inventory for the upcoming week, avoiding overstock or stock shortages and reducing waste.
2. For suppliers, leveraging this data, they can further calculate the reasonable supply volume of ingredients and materials, optimize distribution plans, and mitigate cost increases caused by supply-demand mismatches.
3. This data can also serve as a reference for shops intending to settle in the canteen or merchants seeking to conduct promotions using the canteen venue, providing decision support for formulating marketing or promotion strategies.

1. Data Extraction and Preprocessing:
(1) Data Extraction: Extract the daily chopstick usage volume of relevant canteens from the database of the self-developed 5G Smart Food Safety Industrial Internet of Things (IIoT) Digital Management Platform, including date, canteen ID, location, and today's chopstick usage volume.
(2) Data Preprocessing: Clean the extracted data to remove duplicate, erroneous, or irrelevant information to facilitate subsequent analysis and modeling.

2. Predict Future Dining Patronage of Canteens Based on Chopstick Usage Volume:
(1) Calculate the average chopstick usage volume of the current and prior periods: Use the SUM function to accumulate the chopstick usage volume of the current period (the 7 consecutive days including today) and the prior period (days 8 to 14 prior to today) respectively; Average chopstick usage volume of the current period (7 consecutive days including today) = Current accumulated volume ÷ 7; Average chopstick usage volume of the prior period (days 8 to 14 prior to today) = Prior accumulated volume ÷ 7.
(2) Calculate the change rate of average chopstick usage volume between the current and prior periods, as well as the average change rate of the three most recent prior periods: Change rate of average chopstick usage volume between current and prior periods = (Current average chopstick usage volume - Prior average chopstick usage volume) ÷ Current average chopstick usage volume × 100%; Average change rate of the three most recent prior periods = Sum of the average change rates of the three most recent prior periods ÷ 3.
(3) Establish the next-period dining patronage prediction model: Predicted average chopstick usage volume for the next 7 days = Current average chopstick usage volume × (1 + Average change rate of the three most recent prior periods); Predicted dining patronage for the next 7 days = Predicted average chopstick usage volume for the next 7 days × 7.

搜集汇总

数据集介绍

特点

该数据集是一个用于预测食堂就餐人数的企业数据，包含日期、食堂编号、用筷数量等关键信息，数据规模为757条，每日更新。主要应用于食堂运营规划、供应商配送优化和商家营销策略制定。