Correction: Bhushan et al. Dynamic K-Decay Learning Rate Optimization for Deep Convolutional Neural Network to Estimate the State of Charge for Electric Vehicle Batteries. Energies 2024, 17, 3884

Authors

Kok Soon Tey (ORCID: https://orcid.org/0000-0001-6018-3978)
Alex Stojcevski (ORCID: https://orcid.org/0000-0002-3584-6597)
Mehdi Seyedmahmoudian (ORCID: https://orcid.org/0000-0002-2538-4077)
Neha Bhushan
Saad Mekhilef (ORCID: https://orcid.org/0000-0001-8544-8995)
Mohamed Shaaban (ORCID: https://orcid.org/0000-0002-8267-7490)

Institutions

National Chung Cheng University (TW)
Singapore Science Park (SG)
University of Malaya (MY)
Swinburne University of Technology (AU)

Publication Details

Journal: Energies
Published: 2026-06-18
DOI: https://doi.org/10.3390/en19122880
Primary Topic: Advanced Battery Technologies Research
Type: article
Field-Weighted Citation Impact: 0.00

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article

Correction: Bhushan et al. Dynamic K-Decay Learning Rate Optimization for Deep Convolutional Neural Network to Estimate the State of Charge for Electric Vehicle Batteries. Energies 2024, 17, 3884

Kok Soon Tey, Alex Stojcevski, Mehdi Seyedmahmoudian, Neha Bhushan et al.

Jun 18, 2026

Energies

Advanced Battery Technologies Research

article

Correction: Bhushan et al. Dynamic K-Decay Learning Rate Optimization for Deep Convolutional Neural Network to Estimate the State of Charge for Electric Vehicle Batteries. Energies 2024, 17, 3884

Kok Soon Tey, Alex Stojcevski, Mehdi Seyedmahmoudian, Neha Bhushan, Saad Mekhilef, Mohamed Shaaban

June 18, 2026article en

Abstract

No abstract available for this paper.

EnergiesVol. 19(12)

National Chung Cheng University (TW), Singapore Science Park (SG), University of Malaya (MY), Swinburne University of Technology (AU)

Affordable and clean energy

Openalex Percentile: Top 10%

Advanced Battery Technologies Research

DOI Open Access PDF OpenAlex

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