By Diego Galar Pascual
Artificial Intelligence instruments: selection help platforms in situation tracking and Diagnosis discusses a number of white- and black-box methods to fault prognosis in situation tracking (CM). This vital resource:
- Addresses nearest-neighbor-based, clustering-based, statistical, and data theory-based techniques
- Considers the advantages of every strategy in addition to the problems linked to real-life application
- Covers type tools, from neural networks to Bayesian and help vector machines
- Proposes fuzzy good judgment to give an explanation for the uncertainties linked to diagnostic methods
- Provides info units, pattern signs, and MATLAB® code for set of rules testing
Artificial Intelligence instruments: selection aid structures in situation tracking and analysis delivers an intensive assessment of the newest AI instruments for CM, describing the commonest fault prognosis concepts used and the information received while those innovations are applied.
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Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and DIagnosis by Diego Galar Pascual