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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/1212

Title: Performance Comparison of MATLAB and Neuro Solution Software on Estimation of Fuel Economy by Using Artificial Neural Network
Authors: Serhad Soyhan, Hakan
Emre Kilic, Mehmet
Gokalp, Burak
Taymaz, Imdat
Keywords: Artificial Neural Network
Fuel Economy
MATLAB
Issue Date: 2009
Publisher: Institute of Information Theories and Applications FOI ITHEA
Abstract: In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.
URI: http://hdl.handle.net/10525/1212
ISSN: 1313-0455
Appears in Collections:Book 09 Intelligent Processing

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