DOIONLINE

DOIONLINE NO - IJAECS-IRAJ-DOIONLINE-18009

Publish In
International Journal of Advances in Electronics and Computer Science-IJAECS
Journal Home
Volume Issue
Issue
Volume-8,Issue-5  ( May, 2021 )
Paper Title
Opinion Analysis on Electric Vehicles using Machine Learning Algorithms
Author Name
Aradhya Agrawal, Ayush Jain, Prasanna Kapse, Devesh Sharma
Affilition
Assistant Professor Department of Computer Science and Engineering, Medi-Caps University, Indore, India
Pages
44-49
Abstract
An electric motor runs the electric vehicle, there is no role of the engine which runs by fuel and gases. Vehicle replacement is necessary for these vehicles because of depleting natural resources, pollution increase, global warming, and other environmental problems. The concept of an electric vehicle is not new it has been for a long time, but the immerging concern and awareness of people for carbon footprint has ignited the interest in an electric vehicle. There is a continuing increase in the number of EVs in use, but the major problem arises on the topic of whether consumers accept Electric vehicles over motor vehicles or not. To study the intention of consumers regarding the purchase of Electric Vehicles by Indians, there is a need to know the factors that influence the consumer's mindset. For this, we have made a survey form, which contains questions related to personal traits and views about EVs. We took responses from 91 peoples include students, businessmen. We are focusing on data pre-processing by which we will be converting various values which are in characters or strings are converted to float or integers. Secondly, we are using Matplotlib for Data Visualization i.e., making different types of graphs to visually check the factor that influences the consumer's perception. As a result, the factors that influence the consumer mindset regarding the acceptance of Electric Vehicles are based on the economic and Unavailability of charging stations. Whereas, after applying the machine learning algorithm we get 83.33% accuracy using SVM. Keywords - Electric Vehicles, Classification, Environmental Problems, Motor Vehicles, CO2 Emissions, SVM Support Vector Machines.
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