基于极限学习机神经网络的买断制加盟模式订货决策

Study on Ordering Decision under“Buyout”Franchise Mode Based on Extreme Learning Machine Neural Network

随着服装市场和服装品牌的不断成熟以及人们对服装需求的日益多样化,买断制加盟模式成为具有一定市场知名度的品牌服装的选择,这给加盟商订货决策带来了一定的风险。为了更好地完成订货采购任务,加盟商需根据自己店铺的历史销售数据进行预测,以确定订货会的订货量并制定采购预算。以预测某品牌加盟商夏季每月每个品类的销售量为出发点构建模型,采用极限学习机神经网络的方法进行销售预测,并将预测结果以图表的形式进行展示,为服装加盟商订货决策及采购预算的确定提供理论支持。

As clothing market and fashion brands continue to be mature and demands for clothing are increasingly diversified,＂buyout＂franchise mode has become a selection for clothing brands that possess certain popularity and market share.This brings about certain risks for franchisees＇ordering decisions.To better accomplish the purchasing task,franchisees need to make predictions based on historical sales data of their own stores so as to determine ordering quantity in the order fair and make procurement budget.This paper starts from predicting monthly sales volume of each category of a brand in summer to construct a model and adopts extreme learning machine neural network for sales prediction.The prediction results are displayed in graph form to provide theoretical support for ordering decision and of clothing franchisees and confirmation of procurement budget.