Predicting the Future of Car Manufacturing Industry
using Data Mining Techniques
D. Hanumanthappa, and S. K. International Journal on Information Technology IJIT, 1 (2):
3(September 2011)
Abstract
Data mining helps to find predictive information
from large databases. Companies use predictive modeling tools
for strategic decision-making. It helps companies to identify
and account for the key assumptions that drive business
value—enabling good decision making that leads to
predictable results. By analyzing the company’s historical
information we can anticipate these changes. This paper aims
at providing a proposed data mining solution that can be used
for automotive market, especially in the car manufacturing
domain. That is to predict the future sales on the base of
historical data. Especially we aim at finding the number of
cars to be manufactured by a car manufacturing company by
using the previous years data. For this linear regression
analysis technique is used.
%0 Journal Article
%1 drmhanumanthappa12011predicting
%A Hanumanthappa, Dr. M
%A K, Sarakutty T
%D 2011
%E Das, Dr.Vinu V
%J International Journal on Information Technology IJIT
%K Data_Mining Predictive_Modeling WEKA
%N 2
%P 3
%T Predicting the Future of Car Manufacturing Industry
using Data Mining Techniques
%U http://doi.searchdl.org/01.IJIT.1.2.150
%V 1
%X Data mining helps to find predictive information
from large databases. Companies use predictive modeling tools
for strategic decision-making. It helps companies to identify
and account for the key assumptions that drive business
value—enabling good decision making that leads to
predictable results. By analyzing the company’s historical
information we can anticipate these changes. This paper aims
at providing a proposed data mining solution that can be used
for automotive market, especially in the car manufacturing
domain. That is to predict the future sales on the base of
historical data. Especially we aim at finding the number of
cars to be manufactured by a car manufacturing company by
using the previous years data. For this linear regression
analysis technique is used.
@article{drmhanumanthappa12011predicting,
abstract = {Data mining helps to find predictive information
from large databases. Companies use predictive modeling tools
for strategic decision-making. It helps companies to identify
and account for the key assumptions that drive business
value—enabling good decision making that leads to
predictable results. By analyzing the company’s historical
information we can anticipate these changes. This paper aims
at providing a proposed data mining solution that can be used
for automotive market, especially in the car manufacturing
domain. That is to predict the future sales on the base of
historical data. Especially we aim at finding the number of
cars to be manufactured by a car manufacturing company by
using the previous years data. For this linear regression
analysis technique is used.
},
added-at = {2012-09-24T06:24:05.000+0200},
author = {Hanumanthappa, Dr. M and K, Sarakutty T},
biburl = {https://www.bibsonomy.org/bibtex/2eb0eda7a763bd97c13b117e65519b2ce/ideseditor},
editor = {Das, Dr.Vinu V},
interhash = {7e53362f9e815494ba33270624f7b9bd},
intrahash = {eb0eda7a763bd97c13b117e65519b2ce},
journal = {International Journal on Information Technology [IJIT]},
keywords = {Data_Mining Predictive_Modeling WEKA},
month = {September},
number = 2,
pages = 3,
timestamp = {2012-09-24T06:24:05.000+0200},
title = {Predicting the Future of Car Manufacturing Industry
using Data Mining Techniques
},
url = {http://doi.searchdl.org/01.IJIT.1.2.150},
volume = 1,
year = 2011
}