Enhancing State of Charge Estimation in Ni-MH Batteries Through a Hybrid Approach Incorporating RRBF and K-Means-Reference-Cited by-同舟云学术

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Enhancing State of Charge Estimation in Ni-MH Batteries Through a Hybrid Approach Incorporating RRBF and K-Means

Published:2023-12-01 Issue: Volume:464 Page:01-06
ISSN:
Container-title:2023 IEEE Third International Conference on Signal, Control and Communication (SCC)
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Author:

Souidi Donya¹,Chrouta Jaouher¹,Telmoudi Achraf Jabeur¹

Affiliation:

1. University of Tunis,Laboratory LISIER,Tunis,Tunisia,1008

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10527407/10527456/10527572.pdf?arnumber=10527572

Reference24 articles.

1. Environmentally friendly recycling of spent Ni–MH battery anodes and electrochemical characterization of nickel and rare earth oxides obtained by sol–gel synthesis

2. A recurrent RBF neural network based on adaptive optimum steepest descent learning algorithm

3. Atouts et dfis des batteries Nickel-Mtal Hydrure Ni-MH;Judith;L’ Actualit Chimique,2021

4. Réseaux de neurones récurrents à fonctions de base radiales : RRFR Application au pronostic

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