Yu-Tong Chu

A Training-Enhanced NILMFormer for Non-Intrusive Load Disaggregation Under Diverse Appliance Load Structures

Existing sliding-window deep-learning models for non-intrusive load disaggregation typically use a unified training objective and fixed training configurations, which limits their ability to accommodate structural differences among appliance loads. To address this limitation, this article proposes a training-enhanced N...