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Forecasting Automobile Retail Sales Using Data Mining: The Case of Ranchi, Jharkhand, India

Gyaneshwar Mahto1 , Umesh Prasad2 , Rajiv Kumar Dwivedi3

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 572-574, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.572574

Online published on Sep 30, 2018

Copyright © Gyaneshwar Mahto, Umesh Prasad, Rajiv Kumar Dwivedi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Gyaneshwar Mahto, Umesh Prasad, Rajiv Kumar Dwivedi, “Forecasting Automobile Retail Sales Using Data Mining: The Case of Ranchi, Jharkhand, India,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.572-574, 2018.

MLA Style Citation: Gyaneshwar Mahto, Umesh Prasad, Rajiv Kumar Dwivedi "Forecasting Automobile Retail Sales Using Data Mining: The Case of Ranchi, Jharkhand, India." International Journal of Computer Sciences and Engineering 6.9 (2018): 572-574.

APA Style Citation: Gyaneshwar Mahto, Umesh Prasad, Rajiv Kumar Dwivedi, (2018). Forecasting Automobile Retail Sales Using Data Mining: The Case of Ranchi, Jharkhand, India. International Journal of Computer Sciences and Engineering, 6(9), 572-574.

BibTex Style Citation:
@article{Mahto_2018,
author = {Gyaneshwar Mahto, Umesh Prasad, Rajiv Kumar Dwivedi},
title = {Forecasting Automobile Retail Sales Using Data Mining: The Case of Ranchi, Jharkhand, India},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {572-574},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2910},
doi = {https://doi.org/10.26438/ijcse/v6i9.572574}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.572574}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2910
TI - Forecasting Automobile Retail Sales Using Data Mining: The Case of Ranchi, Jharkhand, India
T2 - International Journal of Computer Sciences and Engineering
AU - Gyaneshwar Mahto, Umesh Prasad, Rajiv Kumar Dwivedi
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 572-574
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

In this article, sales forecast models for the automobile market are developed and tested. Enhanced sales forecast methodologies and models for the automobile market are presented. The methods used deliver highly accurate predictions while maintaining the ability to explain the underlying model at the same time. The representation of the economic training data is discussed, as well as its effects on the newly registered automobiles to be predicted. Our most important criteria for the assessment of these models are the quality of the prediction as well as an easy explicability.The automobile market are presented for the evaluation of the forecast models. The market demand for vehicles has increased in recent years everywhere in the world. We need suitable models to understand and forecast demand of vehicle. This study presents a singular spectrum analysis (SSA) as a univariate time-series model and vector autoregressive model (VAR) as a multivariate model. Empirical results suggest that SSA satisfactorily indicates the evolving trend and provides reasonable results. The VAR model, which comprised exogenous parameters related to the market on a monthly basis, can significantly improve the prediction accuracy. The vehicles sales in beautiful city Ranchi, Capital of Jharkhand, India, are predicted in both short term (up to December 2018) and long term (up to 2021), as proofs of the growth of the Motor Vehicles industry.

Key-Words / Index Term

Sales Forecast; Automobile Industry; Information Technology; Retail; Decision Making; Data Mining; Business Environment; Retail Sales Forecasting; Vehicles Sales

References

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