DocumentCode
2862381
Title
MPG Prediction based on BP Neural Network
Author
Meng, Jun ; Liu, Xiangyin
Author_Institution
Sch. of Electr. Eng., Zhejiang Univ., Hangzhou
fYear
2006
fDate
24-26 May 2006
Firstpage
1
Lastpage
3
Abstract
In this article, we use the data mining theory to construct a BP neural network model to predict MPG (mile per gallon). Based on the nonlinear properties of the six variables given, considering the imperfection using two main variables at the same time, we´ve processed the problem via data preparation, model selection, construction, modification and error comparison as well as model adaption period. At the end of this article, we´ve discussed the principles of acquiring proper parameters based on the distinctions of the neural network chosen and give some possible improving directions. In this manner, in case the original data is given, the predicted MPG result comes out automatically and satisfactorily
Keywords
backpropagation; data mining; data preparation; neural nets; BP neural network; data mining theory; data preparation; error comparison; mile per gallon; model selection; nonlinear properties; Acceleration; Automobiles; Data mining; Engine cylinders; Input variables; Mathematical model; Neural networks; Neurons; Predictive models; Problem-solving;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications, 2006 1ST IEEE Conference on
Conference_Location
Singapore
Print_ISBN
0-7803-9513-1
Electronic_ISBN
0-7803-9514-X
Type
conf
DOI
10.1109/ICIEA.2006.257357
Filename
4025958
Link To Document