In the current post-pandemic era, takeout delivery still plays an important role in our daily life. At the same time, the new challenge facing O2O takeout delivery is how to ensure the safe and efficient delivery of the order within the specified time in the process of delivery. This paper mainly studies the optimization of delivery process based on machine learning support vector regression SVR algorithm. This paper proposes a regional takeout order demand prediction model based on SVR algorithm. The model can effectively predict the order demand in each business area within the next hour, which provides a basis for the intelligent scheduling of the delivery system of the takeout platform. The order data of a delivery platform in Dalian area are used to verify the prediction model, and the prediction results are compared with BP neural network and GA algorithm. The experimental results show that the prediction results of SVR algorithm have better fitting effect, which can effectively predict the order demand of the delivery platform in the region.

Zhaoyang Wu. Optimization of Delivery Process Based on Machine Learning Support Vector Regression SVR Algorithm. Machine Learning Theory and Practice (2020), Vol. 1, Issue 2: 28-36. https://doi.org/10.38007/ML.2020.010204.

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