锂电池健康状态预测的对抗性防御框架

Neural networks are subject to malicious data poisoning attacks affecting the ability of the model to make accurate predictions. The attacks are generated using adversarial techniques imperceptible to the human eye since they use minimal noise to alter features, which end up affecting boundary decisions of the prediction model. Predicting the state of health (SOH) of lithium-ion batteries in an ad...