Using artificial neural networks to detect risk of vehicle failure

David Sanders

    Research output: Contribution to journalArticlepeer-review

    Abstract

    This short paper presents a method (suggested elsewhere) that considers control sensor data and uses it to set fault thresholds. ANNs analyze correlations of data and detect risks. Simulation suggests that vehicle faults can be detected within datasets
    Original languageEnglish
    Pages (from-to)245-246
    JournalJournal of Intelligent Mobility
    Volume14
    Issue number1
    Publication statusPublished - 2011

    Keywords

    • ANN, sensor, vehicle, fault

    Fingerprint

    Dive into the research topics of 'Using artificial neural networks to detect risk of vehicle failure'. Together they form a unique fingerprint.
    • Wheel driven mobile robots

      Sanders, D.

      15/10/09 → …

      Project: Research

    Cite this