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Using artificial neural networks to detect risk of vehicle failure

Research output: Contribution to journalArticlepeer-review

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Using artificial neural networks to detect risk of vehicle failure. / Sanders, David.

In: Journal of Intelligent Mobility, Vol. 14, No. 1, 2011, p. 245-246.

Research output: Contribution to journalArticlepeer-review

Harvard

Sanders, D 2011, 'Using artificial neural networks to detect risk of vehicle failure', Journal of Intelligent Mobility, vol. 14, no. 1, pp. 245-246.

APA

Sanders, D. (2011). Using artificial neural networks to detect risk of vehicle failure. Journal of Intelligent Mobility, 14(1), 245-246.

Vancouver

Sanders D. Using artificial neural networks to detect risk of vehicle failure. Journal of Intelligent Mobility. 2011;14(1):245-246.

Author

Sanders, David. / Using artificial neural networks to detect risk of vehicle failure. In: Journal of Intelligent Mobility. 2011 ; Vol. 14, No. 1. pp. 245-246.

Bibtex

@article{82f12768ab7b44c8a0f6f1c26bb49eda,
title = "Using artificial neural networks to detect risk of vehicle failure",
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",
keywords = "ANN, sensor, vehicle, fault",
author = "David Sanders",
year = "2011",
language = "English",
volume = "14",
pages = "245--246",
journal = "Journal of Intelligent Mobility",
issn = "1472-7633",
number = "1",

}

RIS

TY - JOUR

T1 - Using artificial neural networks to detect risk of vehicle failure

AU - Sanders, David

PY - 2011

Y1 - 2011

N2 - 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

AB - 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

KW - ANN, sensor, vehicle, fault

M3 - Article

VL - 14

SP - 245

EP - 246

JO - Journal of Intelligent Mobility

JF - Journal of Intelligent Mobility

SN - 1472-7633

IS - 1

ER -

ID: 1766924