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| Predicting MPG for Automobile Using Artificial Neural Network Analysis |
Mohammed N. Jamala, Samy S. Abu-Naser
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Abstract:
During the course of this research, imposing the training of an artificial neural network to predicate the MPG rate for present thru forthcoming automobiles in the foremost relatively accurate evaluation for the approximated number which foresight the actual number to help through later design and manufacturing of later automobile, by training the ANN to accustom to the relationship between the skewing of each later stated attributes, the set of mathematical combination of the sequences that could be excavate the Miles Per Gallon(MPG) by the system and using both the Gradient Descent Algorithm and the Normalized Square Error Technique explicitly lure the Final Parameter Norm and Scaling layer and Bounded Layering rules implicitly. And so on the system should be able to produce immune approximations `and calculations to make better of results of What the Actual output estimation.
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