Abstract: During mission, determining priority categories of maintenance task rationally and scientifically is valuable to effectiveness and efficiency of maintenance support. A priority sorting approach of maintenance task during mission based on BP neural networks is proposed. Modeling process of neural networks model is discussed in detail, and it focuses on model design that includes input data preparation, output data preparation and neural networks structure. Through training of input and output, established neural networks can learn complex relationship between criteria and priority of maintenance tasks, obtain preference of decision makers, help decision maker sort maintenance tasks according to their priority.

Key words: Back-Propagation（BP） neural networks, maintenance task, priority, sorting

摘要： 在任务执行期合理、科学地确定维修任务的优先级别对于有序、高效地组织维修保障活动具有重要意义。提出了一种基于BP神经网络的维修任务优先级分类方法。详细介绍了神经网络模型的建模过程，其中重点介绍了模型设计，包括输入数据准备、输出数据准备与神经网络结构。所建立的神经网络模型通过对输入与输出的训练，可以学习准则与维修任务优先级之间的复杂关系，获得并表示决策者的偏好，有效地辅助决策者对维修任务优先级进行分类。

关键词: 向后传播（BP）神经网络, 维修任务, 优先级, 分类