Adaptive fault detection and diagnosis using parsimonious Gaussian mixture models trained with distributed computing techniques.
Thiago Akio NakamuraReinaldo M. PalharesWalmir M. CaminhasBenjamin Rodrigues de MenezesMário César Mello de Massa CamposUbirajara FumegaCarlos H. de M. BomfimAndré P. LemosPublished in: J. Frankl. Inst. (2017)
Keyphrases
- distributed computing
- gaussian mixture model
- fault detection and diagnosis
- mixture model
- distributed environment
- fault diagnosis
- distributed systems
- mobile agents
- speaker recognition
- grid computing
- cloud computing
- fault tolerance
- em algorithm
- fault detection
- expectation maximization
- virtual machine
- feature vectors
- maximum likelihood
- peer to peer
- fault tolerant
- mobile communications
- power plant
- distributed computing environment
- database systems
- knowledge base
- feature extraction
- expert systems
- databases
- training set
- neural network