Research on Optimal Model Combination of Cross-Border E-Commerce Platform Operation Relying on Robot Hybrid Algorithm

Cross-Border E-Commerce (CBEC) has evolved significantly due to the global growth of the Internet, becoming a crucial global market. As e-commerce integrates into daily life and work, the market has transitioned from incremental growth to a more sophisticated landscape. Enhancing user conversion rates is pivotal for retail E-commerce, setting the stage for intense competition among enterprises. The swift evolution of EC has empowered users with information production and self-dissemination capabilities, reshaping traditional production and market response norms. CBEC platforms focus on user-centric operations to align with societal development. This paper explores hybrid algorithms, ultimately selecting the fuzzy analytic hierarchy process for assessing operational performance in CBEC platforms. Finally, this paper conducts empirical research, and the fuzzy comprehensive evaluation score is [82.71 79.95 78.84 79.42 83.35 82.68]. Through the mining and prediction of user consumption behavior data, we can scientifically analyze the platform operation performance, which can find high potential users and conduct accurate operation.