Bibtex de la publication

@InProceedings{ Sa2015.7,
author = {Salameh, Farah and Picot, Antoine and Chabert, Marie and Leconte, Eve and Ruiz-Gazen, Anne and Maussion, Pascal},
title = "{Variable Importance Assessment in Lifespan Models of Insulation Materials: A Comparative Study (regular paper)}",
booktitle = "{IEEE International Symposium on Diagnostics, Power Electronics and Drives (SDEMPED), Guarda, Portugal, 01/09/2015-04/09/2015}",
year = {2015},
month = {septembre},
publisher = {IEEE},
address = {},
pages = {(electronic medium)},
language = {anglais},
URL = {},
keywords = {design of experiments, lifespan, modeling, random forest, regression tree, response surface, outliers, twisted pairs, variable importance},
abstract = {This paper presents and compares different methods for evaluating the relative importance of variables involved in insulation lifespan models. Parametric and non-parametric models are derived from accelerated aging tests on twisted pairs covered with an insulating varnish under different stress constraints (voltage, frequency and temperature). Parametric models establish a simple stress-lifespan relationship and the variable importance can be evaluated from the estimated parameters. As an alternative approach, non-parametric models explain the stress-lifespan relationship by means of regression trees or random forests (RF) for instance. Regression trees naturally provide a hierarchy between the variables. However, they suffer from a high dependency with respect to the training set. We show that RF provide a more robust model while allowing a quantitative variable importance assessment. Comparisons of the different models are performed on different training and test sets obtained through experiments.}