串收番茄批发价格预测分析数据

下游零售商、水果连锁店可以根据串收番茄价格预测趋势，在价格低点时增加采购量，在高点时减少采购量，从而显著降低采购成本。同时结合销售预测，企业可以制定更优的库存策略。例如，当预测价格即将上涨时，可适当增加安全库存；当预测价格下跌时，则加速出货、减少库存积压，实现“精益库存”。另外，短期价格预测有助于物流公司预判市场活跃度，合理调配冷链运输资源，优化仓储布局。1.数据采集：企业以“国研掌上果贸结算通平台”的真实交易数据为基础，汇总并提取出预测分析日前7日的串收番茄批发价格历史数据，从而构建出时间序列数据集。 2. 数据预处理：对数据进行清洗，去除缺失值和异常数据。3. 数据分析： 使用加权移动平均法。T= （T-1*7+T-2*6+T-3*5+T-4*4+T-5*3+T-6*2+T-7*1）/7+6+5+4+3+2+1 T:T日建议批发价格即预测分析日当日建议批发价格（件/元)； T-1：预测分析日前一日批发价格（件/元)； T-2: 预测分析日前二日批发价格（件/元)…… T-7：预测分析日前七日批发价格（件/元)。Downstream retailers and fruit store chains can leverage truss tomato price trend forecasts to adjust procurement volumes: increase purchases at low price points and reduce purchases at high price points, thereby significantly lowering procurement costs. Combined with sales forecasts, enterprises can formulate more optimized inventory strategies. For instance, when prices are forecast to rise, appropriate safety stock can be increased; when prices are forecast to fall, enterprises can accelerate shipments and reduce inventory backlogs to achieve "lean inventory". Additionally, short-term price forecasts help logistics companies anticipate market activity, rationally allocate cold chain transportation resources, and optimize warehouse layout. 1. Data Collection: Based on real transaction data from the Guoyan Zhangshang Guomao Jiesuantong Platform, enterprises aggregate and extract 7-day historical wholesale price data of truss tomatoes prior to the forecast analysis date to construct a time-series dataset. 2. Data Preprocessing: Clean the dataset by removing missing values and outliers. 3. Data Analysis: The weighted moving average method is adopted, with the calculation formula as follows: T = (T-1*7 + T-2*6 + T-3*5 + T-4*4 + T-5*3 + T-6*2 + T-7*1) / (7 + 6 + 5 + 4 + 3 + 2 + 1) Where T represents the recommended wholesale price on day T, i.e., the recommended wholesale price on the forecast analysis date (unit: yuan per piece); T-1 is the wholesale price one day prior to the forecast analysis date (yuan per piece); T-2 is the wholesale price two days prior to the forecast analysis date (yuan per piece); and so on, up to T-7, which is the wholesale price seven days prior to the forecast analysis date (yuan per piece).

搜集汇总

背景与挑战

背景概述

该数据集是一个用于预测串收番茄批发价格的时间序列数据集，包含615条记录，每年更新一次，数据结构涵盖日期、果品名称、过去7天的历史价格以及当日预测价格。它基于企业真实交易数据，采用加权移动平均算法进行价格预测，主要应用于下游零售商、水果连锁店和物流公司的采购成本优化、库存管理和资源调配场景。