基于Grey-Markov的生鲜配送需求量预测系统

Design of Fresh Agricultural Products Distribution Demand Prediction System Based on Grey-Markov Model

对生鲜农产品配送需求量进行预测,实现按需配送,可以降低甚至实现生鲜农产品的零库存,减少生鲜农产品变质、腐烂等损耗。为了高效预测生鲜农产品配送需求量,提出一种基于Grey-Markov的生鲜配送需求量预测系统。系统以Grey-Markov为预测模型,对生鲜农产品下一日的配送需求量进行预测,与指数回归等预测模型相比,Grey-Markov模型具有更强的稳定性和更好的准确性。系统设计采用C/S架构,实现以按需配送为目标的原始数据导入、原始数据管理、历史销量分析、需求量预测等功能。详细介绍了系统的架构设计、功能设计、数据库设计和程序设计。测试与应用结果表明,系统实现了预期的功能,应用效果良好,可有效减少生鲜农产品的损耗。与使用系统前相比,日剩余未售出生鲜农产品总量可降低20百分点以上。

Predicting the distribution demand of fresh agricultural products can realize on-demand distribution which can reduce or even realize the zero inventory of fresh agricultural products and reduce the deterioration,decay and other losses of fresh agricultural products.In order to efficiently predict the distribution demand of fresh agricultural products,a fresh agricultural products distribution demand prediction system based on Grey-Markov model is proposed.The system takes Grey-Markov model as the prediction model to predict the distribution demand of fresh agricultural products in the next day.Compared with the prediction models such as exponential regression model,Grey-Markov model has stronger stability and better accuracy.The system adopts C/S architecture and realizes the functions of original data import,original data management,historical sales analysis and demand prediction aimed at on-demand distribution.The architecture design,function design,database design and program design in such system are introduced in detail.The test and application results show that such system realizes the expected function,with excellent application effect,and can effectively reduce the loss of fresh agricultural products.Compared with before using the system,the total daily remaining unsold fresh agricultural products can decrease by more than 20%.