early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks.
Minzhen WenMesfin S. IbrahimAbdulmelik Husen MedaGuoqi ZhangJiajie FanPublished in: Expert Syst. Appl. (2024)
Keyphrases
- recurrent neural networks
- anomaly detection
- long short term memory
- high power
- intrusion detection
- low power
- neural network
- anomalous behavior
- high density
- detecting anomalies
- feed forward
- network intrusion detection
- network traffic
- complex valued
- power supply
- intrusion detection system
- artificial neural networks
- echo state networks
- power consumption
- energy consumption
- detect anomalies
- network anomaly detection
- low cost
- one class support vector machines
- negative selection algorithm
- image segmentation
- unsupervised learning
- support vector
- real time