Predicting Car Mileage per Gallon
International Journal of Advanced Science and Technology 124 (124):51-59 (2015)
Abstract
In this paper an Artificial Neural Network (ANN) model was used to help cars dealers
recognize the many characteristics of cars, including manufacturers, their location and
classification of cars according to several categories including: Make, Model, Type,
Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway,
Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per
gallon when the car is driven in the city(MPG_City). The results showed that ANN model
was able to predict MPG_City with 97.50 % accuracy. The factor of DriveTrain has the
most influence on MPG_City evaluation. Similar studies can be carried out for the
evaluation of other characteristics of cars.
Keywords
Categories
No categories specified
(categorize this paper)
(categorize this paper)
PhilPapers/Archive ID
AFAPCM
Upload history
Archival date: 2019-12-11
View other versions
View other versions
Added to PP index
2019-12-11
Total views
74 ( #58,008 of 71,190 )
Recent downloads (6 months)
21 ( #37,796 of 71,190 )
2019-12-11
Total views
74 ( #58,008 of 71,190 )
Recent downloads (6 months)
21 ( #37,796 of 71,190 )
How can I increase my downloads?
Downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.