Description

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:

  • Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques
  • Considers the merits of each technique as well as the issues associated with real-life application
  • Covers classification methods, from neural networks to Bayesian and support vector machines
  • Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes
  • Provides data sets, sample signals, and MATLAB® code for algorithm testing

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and DIagnosis

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£175.00

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Hardback by Diego Galar Pascual

1 in stock

Short Description:

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis... Read more

    Publisher: Taylor & Francis Inc
    Publication Date: 22/04/2015
    ISBN13: 9781466584051, 978-1466584051
    ISBN10: 146658405X

    Number of Pages: 549

    Non Fiction , Technology, Engineering & Agriculture , Education

    • Tell a unique detail about this product4

    Description

    Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:

    • Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques
    • Considers the merits of each technique as well as the issues associated with real-life application
    • Covers classification methods, from neural networks to Bayesian and support vector machines
    • Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes
    • Provides data sets, sample signals, and MATLAB® code for algorithm testing

    Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

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