In recent years, with the change of people’s living habits, food delivery has become more and more popular. Along with this is the rapid growth of takeaway distribution. It is significant to improve the accurate prediction of the take-out order quantity since it can reduce unnecessary losses for the merchants. The Cloud computing system is the main platform for processing massive data. Applying cloud computing resource scheduling to the forecasting of takeaway orders will greatly help merchants. The research purpose of this paper is to study the cloud-computing resource scheduling based on improved ANN model takeaway order volume prediction. This paper improves the ANN model and proposes a cloud computing resource scheduling method based on improved ANN model takeaway order volume prediction. An experimental test was performed to verify the reliability of the proposed method. The results of this study show that the proposed method can accurately predict takeaway orders and contributes to reasonable resource scheduling.

中文翻译：

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基于改进的神经网络模型外卖订单量预测的云计算资源调度

近年来，随着人们生活习惯的变化，送餐越来越流行。随之而来的是外卖配送的快速增长。重要的是，提高取出订单数量的准确预测，因为它可以减少商人不必要的损失。云计算系统是处理海量数据的主要平台。将云计算资源调度应用于外卖订单的预测将极大地帮助商家。本文的研究目的是研究基于改进的神经网络模型外卖订单量预测的云计算资源调度。本文对人工神经网络模型进行了改进，提出了一种基于改进的人工神经网络外卖订单量预测的云计算资源调度方法。进行了实验测试，以验证所提出方法的可靠性。研究结果表明，该方法可以准确预测外卖订单，有助于合理的资源调度。