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  Published Paper Details:

  Paper Title

DEVELOPMENT OF MACHINE LEARNING MODELS FOR A RAPID BATTERY CHARGER SYSTEM

  Authors

  Ramandeep Kaur,  Amar Singh,  Shakti Kumar

  Keywords

Machine Learning, ANN, KNN, Multi-Regression

  Abstract


Machine learning models are used to solve different nonlinear and complex problems. This paper presents three machine learning approaches to design and develop an intelligent rapid battery charger system. Our intelligent rapid battery system can decide the charging current using two inputs i.e. temperature and temperature gradient. For design purposes, we developed Artificial Neural Networks (ANN), K-Nearest Neighbor (KNN) and Multi-Regression based machine learning models for a rapid battery charger system. We trained all three machine learning models in python. For results, we observe that the performance of ANN outperforms KNN and multi-regression machine learning models.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2205185

  Paper ID - 219499

  Page Number(s) - b681-b687

  Pubished in - Volume 10 | Issue 5 | May 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Ramandeep Kaur,  Amar Singh,  Shakti Kumar,   "DEVELOPMENT OF MACHINE LEARNING MODELS FOR A RAPID BATTERY CHARGER SYSTEM", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 5, pp.b681-b687, May 2022, Available at :http://www.ijcrt.org/papers/IJCRT2205185.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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