Many software failures are those due to the software aging phenomena. In this work, we present a detailed evaluation of our chosen machine learning prediction ...

Adaptive on-line software aging prediction based on Machine Learning. Javier Alonso and Jordi Torres. Barcelona Supercomputing Center. Dept. of Computer ...

Many software failures are those due to the software aging phenomena. In this work, we present a detailed evaluation of our chosen machine learning prediction ...

We have tested our prediction model on a three-tier web J2EE application achieving acceptable prediction accuracy against complex scenarios with small training ...

Share. Adaptive on-line software aging prediction based on Machine Learning. International Conferences 2010. Share page with AddThis. Authors: Alonso, Javier ...

The proposed prediction model uses static thresholding and adaptive thresholding methods. The performance of the algorithms is compared, and it is found that ...

Published on BSC-CNS (https://www.bsc.es). Inicio > Adaptive on-line software aging prediction based on Machine Learning. Adaptive on-line software aging ...

Apr 1, 2022 · In this work, we propose a histogram data-based framework for online adaptive prediction of battery ageing trajectory and lifetime under diverse ...

LSTM can better learn long-term dependent information in battery aging data, and provide more powerful nonlinear mapping capabilities than simple regression ...

Oct 3, 2022 � The classifier proposed in this paper is based on the ensemble learning algorithm in which the KNN algorithm is utilized as the base learner.