SL-DSVDD: Scale learning based deep support vector data description network for EV battery anomaly detection

Chuanjie Liao

doi:10.1016/j.est.2025.118076

SL-DSVDD: Scale learning based deep support vector data description network for EV battery anomaly detection

2025-08-20

0

PRE

AI

DOI：10.1016/j.est.2025.118076

Original

Original request for help

Save

Abstract

En 中文

• A novel scale learning mechanism integrating DSVDD is proposed to address variability and dimensionality issues. • A scale learning block is designed for efficient high-level feature extraction. • A DSVDD module captures low-level and non-distributional features to tackle distributional variability. • Extensive experiments on EV battery datasets demonstrate the framework's robustness, accuracy, and efficiency.

Keywords:

scale learning

DSVDD

feature extraction

distributional variability

EV battery datasets

SL-DSVDD: Scale learning based deep support vector data description network for EV battery anomaly detection

Abstract

Journal

Organization