余杭区水果类农副产品市场需求量预测数据

本数据提供了余杭区水果类农副产品的市场需求预测值，旨在为水果供应链中的各方提供精准的决策支持。1.水果分销商可以利用本预测数据优化进货计划，确保在需求高峰期有充足的库存，同时避免需求低迷时的过剩库存。2.农业合作社可以根据市场需求预测调整种植策略，比如决定增加或减少某些水果的种植面积，以适应市场需求。3.零售商可以依据预测数据调整促销活动，比如在预测显示需求增加的时期推出促销，以吸引更多顾客。4.政府机构可以利用本数据来制定或调整农业支持政策，比如提供种植补贴或技术援助，以促进当地水果产业的发展。因此，本数据的应用不仅有助于提高水果供应链的效率和适应性，还能促进农业产业的可持续发展，确保消费者的需求得到满足。1.数据抽取：从公司农副产品物流运输管理系统里抽取余杭区水果类农副产品的物流运输登记数据，包括运输业务编号、出发地、到达地（仅限余杭区）、出发时间、预计到达时间、运输吨位、水果品种。
2.数据预处理：对抽取的数据进行清洗，去除重复记录，处理缺失值，修正异常数据点。
3.数据加工与分析：（1）计算历史运输量：对于每种水果类农副产品，使用SUMIFS函数对运输吨位进行累加，分别计算出其过去365天、90天和30天的总运输量。（2）建立市场需求量预测模型：①每种水果类农副产品的未来30天市场需求量预测值=（过去365天总运输量÷365×a+过去90天的总运输量÷90×b+过去30天的总运输量÷30×c）÷3×30×k；②系数a、b、c反映数值对未来30天市场需求量预测的影响程度，k用于考虑未在平台进行登记的运输量部分，这些系数均通过市场调研并结合行业专家论证确定，不定期纠正。

This dataset provides market demand forecast values for fruit agricultural and sideline products in Yuhang District, aiming to offer precise decision-making support for all parties in the fruit supply chain. 1. Fruit distributors can use this forecast data to optimize their procurement plans, ensuring sufficient inventory during peak demand periods while avoiding excess inventory when demand is sluggish. 2. Agricultural cooperatives can adjust their planting strategies based on market demand forecasts, such as deciding to increase or decrease the planting area of certain fruits to align with market demand. 3. Retailers can adjust their promotional activities according to the forecast data, for example, launching promotions during periods of predicted increased demand to attract more customers. 4. Government agencies can use this data to formulate or adjust agricultural support policies, such as providing planting subsidies or technical assistance, to promote the development of the local fruit industry. Therefore, the application of this dataset not only helps improve the efficiency and adaptability of the fruit supply chain, but also promotes the sustainable development of the agricultural industry and ensures that consumer demands are met. 1. Data extraction: Extract logistics and transportation registration data of fruit agricultural and sideline products in Yuhang District from the company's agricultural and sideline products logistics transportation management system, including transportation business number, origin, destination (only within Yuhang District), departure time, estimated arrival time, transportation tonnage, and fruit variety. 2. Data preprocessing: Clean the extracted data, remove duplicate records, handle missing values, and correct abnormal data points. 3. Data processing and analysis: (1) Calculate historical transportation volume: For each type of fruit agricultural and sideline product, use the SUMIFS function to accumulate the transportation tonnage, and calculate the total transportation volumes over the past 365 days, 90 days, and 30 days respectively. (2) Establish a market demand forecast model: ① The market demand forecast value for the next 30 days of each fruit agricultural and sideline product = (Total transportation volume over the past 365 days ÷ 365 × a + Total transportation volume over the past 90 days ÷ 90 × b + Total transportation volume over the past 30 days ÷ 30 × c) ÷ 3 × 30 × k; ② The coefficients a, b, and c reflect the degree of influence of the values on the forecast of the 30-day future market demand, and k is used to account for the portion of transportation volume not registered on the platform. These coefficients are determined through market research and combined with industry expert demonstrations, and are corrected irregularly.

搜集汇总

数据集介绍

特点

该数据集提供了余杭区水果类农副产品的市场需求预测数据，包含1587条记录，每日更新。数据涵盖运输业务编号、出发地、到达地、运输吨位、水果品种等信息，并通过历史运输量和预测模型为供应链各方提供精准的决策支持。