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冰箱订单需求具有一些不确定因素,传统的数据模型不能准确描述订单变化规律.预测精度比较低.为了进一步更加准确地预测出冰箱订单需求量,采用了将果蝇算法和灰色理论相结合.构建了一种果蝇优化灰色神经网络的冰箱订单需求预测方法.利用灰色系统理论处理订单产生中的随机性,由果蝇算法对灰色神经网络的参数进行优化,实现对冰箱订单的准确预测.通过两组实验,果蝇算法优化灰色神经网络和灰色神经网络,两者相比较,果蝇算法优化灰色神经网络提高了订单需求的预测精度,为冰箱订单需求的预测提供了依据.
There are some uncertainties in the demand of the refrigerator order, the traditional data model can not accurately describe the order variation law, the prediction accuracy is relatively low.In order to more accurately predict the demand for the refrigerator order, a combination of the Drosophila algorithm and the gray theory is adopted. A fruit flies optimization gray neural network refrigerator order demand forecasting method.Using the gray system theory to deal with the randomness in order generation, the flies algorithm is used to optimize the gray neural network parameters, Two groups of experiments, the fruit fly algorithm optimizes the gray neural network and the gray neural network. Compared with the two, the fruit fly algorithm optimizes the gray neural network to improve the prediction precision of the order demand, which provides the basis for the forecast of the refrigerator order demand.