Over the past decade, representation learning has received particular attention in the intelligent inspection and maintenance of complex systems thanks to its overwhelming advantages in discovering and mining hidden knowledge representations. The room for in-depth investigations of representation learning-related topics remains open, especially explainable approaches for intelligent inspection and maintenance of complex systems. The primary objective of this special issue, entitled “Explainable Representation Learning-based Intelligent Inspection and Maintenance of Complex Systems,” of IEEE Transactions on Neural Networks and Learning Systems is to provide the related latest achievements made by researchers and practitioners on the one hand and to identify critical issues and challenges for future investigation on the other hand.

中文翻译：

---

客座社论：基于可解释表示学习的复杂系统智能检查与维护特刊

在过去的十年中，表示学习由于其在发现和挖掘隐藏知识表示方面的压倒性优势，在复杂系统的智能检查和维护方面受到了特别关注。深入研究表征学习相关主题的空间仍然开放，特别是复杂系统的智能检查和维护的可解释方法。 《IEEE Transactions on Neural Networks and Learning Systems》的本期特刊的主要目的是提供“基于可解释表示学习的复杂系统的智能检查和维护”，一方面提供研究人员和实践者取得的相关最新成果，另一方面提供研究人员和实践者的相关最新成果。另一方面，确定未来调查的关键问题和挑战。