At present, with the continuous development of the intelligent system, it is used in many industries. In e-commerce industry, the intelligent system has also been used, especially in supplier management. Based on the machine learning theory, this paper studies the optimization of the supplier management intelligent system of cross-border e-commerce platforms. Based on the wisdom algorithm and machine learning perspective, the optimization of cross-border e-commerce platform supplier credit system is studied in this paper. Firstly, the calculation of the traditional supplier credit evaluation is optimized by introducing the decision matrix algorithm of the difference matrix and the cloud model evaluation method. Then a multi-objective joint decision model of supplier selection and order allocation is established, and the multi-objective evolutionary algorithm combined with actual examples is applied to verify the effectiveness and feasibility of the algorithm and model. Finally, the decision makers’ preferences are integrated into the intelligent decision-making, and the cloud model evaluation method is adopted. The rough set and gray relational analysis mathematical tools are used to construct the procurement supply evaluation system. The research results show that the comparison of the three general indicators of the procurement supply chain can be obtained through the cloud model evaluation calculation, which indirectly reflects the preference decision weights of the three objective functions of the cross-border e-commerce supplier selection and order allocation multi-objective optimization model. This indicates that the procurement supply evaluation system constructed in this paper has achieved the purpose of scientific evaluation and selection of suppliers, and has played a theoretical reference role for supplier management of cross-border e-commerce platform.

中文翻译：

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基于机器学习的跨境电子商务平台供应商智能管理系统优化研究

当前，随着智能系统的不断发展，它已在许多行业中得到应用。在电子商务行业中，智能系统也已被使用，特别是在供应商管理中。基于机器学习理论，研究了跨境电子商务平台供应商管理智能系统的优化。基于智慧算法和机器学习的观点，研究了跨境电子商务平台供应商信用体系的优化。首先，通过引入差异矩阵的决策矩阵算法和云模型评估方法，优化了传统供应商信用评估的计算方法。然后建立了供应商选择和订单分配的多目标联合决策模型，将多目标进化算法与实例相结合，验证了该算法和模型的有效性和可行性。最后，将决策者的偏好整合到智能决策中，并采用云模型评估方法。运用粗糙集和灰色关联分析数学工具构建了采购供应评价系统。研究结果表明，可以通过云模型评估计算获得采购供应链中三个一般指标的比较结果，这间接反映了跨境电子商务供应商选择和采购三个目标函数的偏好决策权重。订单分配多目标优化模型。