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Showing 1 to 3 of 3 for “"unsupervised neural networks"”.

  1. Data mining, fraud detection and mobile telecommunications: call pattern analysis with unsupervised neural networks

    … to be able to isolate fraudulent usage. An unsupervised learning algorithm can analyse and cluster call patterns for each subscriber in order to facilitate the fraud detection process. This research investigates the unsupervised learning potentials of two neural networks for the profiling of …

    western-cape Repository record for Data mining, fraud detection and mobile telecommunications: call pattern analysis with unsupervised neural networks (opens in a new tab)

  2. Computational intelligence for fault diagnosis in gearbox systems

    … models are employed using supervised and unsupervised neural networks. Both strategies have been implemented to prove the capability of the suggested approach. A cost reduction is performed based on removing the least utilised sensors without losing the performance of the condition …

    nott-trent Repository record for Computational intelligence for fault diagnosis in gearbox systems (opens in a new tab)

  3. Bayesian autoencoders for anomaly detection: Design, uncertainty quantification, and explainability with industrial applications

    … models such as autoencoders (AEs), a class of neural networks (NNs), to achieve state-of-the-art results in anomaly detection. Nevertheless, there are growing concerns regarding the safety and trustworthiness of AEs, as recent studies have reported the surprising failures of AEs on seemingly …

    cambridge Repository record for Bayesian autoencoders for anomaly detection: Design, uncertainty quantification, and explainability with industrial applications (opens in a new tab)