The effectiveness of e-commerce strategic planning determines whether e-commerce can achieve the expected goals and performance. Technology adoption has become the main research idea for research organizations to adopt e-commerce, but the study of strategic planning process is still in its infancy. Construct a supervised machine learning model with strong generalization ability to solve the decision support problem of e-commerce strategic planning more effectively. A decision support method integrating rough set and support vector machine (SVM) is proposed, which is based on a three-stage SVM hybrid model. Decision support method, e-commerce strategic planning crisis early warning decision model is based on parallel meta-heuristic strategy and FKNN. Experiments show that the intelligent decision-making methods proposed in this paper can obtain good performance, and achieve the expected results and objectives, and promote the further development of the machine learning method itself, which has certain theoretical significance and practical application value.

电子商务战略规划的有效性决定了电子商务是否可以实现预期的目标和绩效。技术采用已成为研究组织采用电子商务的主要研究思想，但战略规划过程的研究仍处于起步阶段。构建具有较强泛化能力的有监督的机器学习模型，可以更有效地解决电子商务战略规划的决策支持问题。提出了一种基于三阶段SVM混合模型的粗糙集与支持向量机集成的决策支持方法。决策支持方法，电子商务战略规划危机预警决策模型是基于并行元启发式策略和FKNN的。