Electric Vehicles Acceptance and Knowledge Identification in India using Naive Bayes and k-Nearest Neighbor Classifiers
Vishnu M. R.1, Rahul Ashok2, L. Nitha3
1Vishnu M. R., PG Student, Department of Computer Science and I.T., Amrita School of Arts and Sciences, Kochi, India.
2Rahul Ashok, PG Student, Department of Computer Science and I.T., Amrita School of Arts and Sciences, Kochi, India.
3L. Nitha, Assistant Professor, Department of Computer Science and I.T., Amrita School of Arts and Sciences, Kochi, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 22, 2020. | Manuscript published on March 10, 2020. | PP: 1630-1633 | Volume-9 Issue-5, March 2020. | Retrieval Number: E3008039520/2020©BEIESP | DOI: 10.35940/ijitee.E3008.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In order to identify the effect electric vehicles have made in India, we ensue a survey under trend analysis to find a panacea and overall understanding people have about electric vehicles. We used Naive Bayesian and k-Nearest Neighbor for analyzing customer opinion regarding the use of electric vehicles. As pollutants keep on polluting the aerosphere it’s more and more appropriate to start using electric vehicles. Electric vehicle support in India is low as of now but is expected to have sufficient support as of 2030. The main objective of our research is to identify the electric vehicles acceptance by people and to identify the knowledge people have about electric vehicles. The result was mainly based on retail price and sufficient support being made available. We used Weka 3.8.4 for experimenting the result. The results found out that positive environmental effects on a large amount of customers for choosing electric vehicles. Customer focuses on price and appropriate charging facilities while they choose to buy electric vehicles. In finding the result, the k-nearest neighbor method showed more accurate results than Naive Bayes when done on large datasets.
Keywords: k-Nearest Neighbor classifier, Naïve Bayes Classifier, KDD, Data Mining
Scope of the Article: Data Mining