Research on e-commerce personalised transaction processing model based on reinforcement learning Online publication date: Wed, 16-Aug-2023
by Jinling Chi
International Journal of Computational Systems Engineering (IJCSYSE), Vol. 7, No. 2/3/4, 2023
Abstract: Aiming at increasing the amount of transaction processing issues with the rapid development of the e-commerce industry, this study proposes the personalised transaction processing model of e-commerce based on reinforcement learning. The DBSCAN method is used to pre-process the high-dimensional and low-density data in e-commerce, and the improved DR-PSO method is used to reduce the dimension of the data so as to obtain the optimal data set. Then, an e-commerce transaction processing model is constructed based on learning algorithm and the distributed multi-objective synthetic TOPE algorithm. The research results show that TOPE algorithm is the most economical, which is conducive to the long-term development of e-commerce. The results show that the e-commerce transaction processing system model proposed in this study has high adaptability and effectiveness. This study provides a reference for the progress of e-commerce in the era of artificial intelligence.
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