UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 6
June-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIRFN06017


Registration ID:
404020

Page Number

110-114

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Title

PREDICT THE ENERGY CONSUMPTION EFFICIENCY.

Abstract

The paper mainly aims at the predict the energy consumption efficiency. The energy Consumption has been analysed for electric vehicles there might be a electric bikes and electric cars during the energy consumption have been analysed and predicted in this project. This analyse the energy consumption in the supply chain using the dataset and predictes the year, model and efficiency and gives a prediction. This is analysed using the Random Forest regressor visualization and decision tree.

Key Words

Electric vehicle (EV), machine learning (ML), random forest regression, Decision tree.

Cite This Article

" PREDICT THE ENERGY CONSUMPTION EFFICIENCY.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.110-114, June-2022, Available :http://www.jetir.org/papers/JETIRFN06017.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

" PREDICT THE ENERGY CONSUMPTION EFFICIENCY.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp110-114, June-2022, Available at : http://www.jetir.org/papers/JETIRFN06017.pdf

Publication Details

Published Paper ID: JETIRFN06017
Registration ID: 404020
Published In: Volume 9 | Issue 6 | Year June-2022
DOI (Digital Object Identifier):
Page No: 110-114
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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