基于大数据分析的农产品销售预测系统设计与实现

Implementation of agricultural product sales forecasting system based on big data analysis

针对农产品销售信息不透明的问题,以大连大樱桃销售数据作为具体研究对象,采用数据与趋势、梯度下降趋势方法对销售数据进行分析预测.销售预测系统利用数据埋点技术和数据爬虫技术获取中小电商的销售数据,根据粒度对销售数据进行分层处理,通过梯度下降算法销量预测,并可视化展示预测结果,销量预测系统基本满足了生产和销售决策指导需求,具有较高的实用价值.

In order to solve the problem of opaque sales information of agricultural products,the sales data of Dalian cherries was taken as the specific research object.Analysis and prediction methods of data and trend and gradient downward trend were used to analyze and forecast the sales data.The sales forecasting system utilizes data mining technology and data crawler technology to obtain the sales data of small and medium-sized e-commerce,strategically processes the sales data according to the granularity,forecasts the sales volume through the gradient descent algorithm,and visually displays the forecast results,and the expected effect of sales basically meets the needs of production and sales and the needs of decision-making guidance,which has high practical value.