Self-adaptive non-intrusive load identification method based on random forest

The invention discloses a random forest-based self-adaptive non-intrusive load identification method. The method comprises the steps of establishing an electrical load characteristic database; extracting required load characteristics from each switching event; normalizing the obtained load characteristics to obtain required sample points; processing the sample points by an unknown pattern recognition module, and distributing known labels or unknown labels to the sample points; wherein all labels are known sample points, and obtaining an identification result by using a random forest algorithm;wherein all the labels are unknown sample points and are processed by an online clustering module, and if new clustering is generated, enabling a user to select whether to distribute the class labelsto the cluster or not; performing new clustering with labels, updating the random forest through an online updating module, and updating the existing knowledge through an unknown mode recognition module; and enabling the unkn