To search, Click below search items. |
| All Published Papers Search Service |
|
|
|
Title |
Experimental Analysis of Artificial Neural Networks Used for Function Approximation |
|
Author |
Akram Mustafa |
| Citation |
Vol. 19 No. 9 pp. 82-90 |
|
Abstract |
Artificial neural network (ANN) is a powerful mathematical computational model, which is used in many important life applications such as function approximation, data regression, solving classification problem, pattern recognition and much other application. The objective of this paper is to use ANN for function approximation, to find the relationship from a given finite input-output data, that using in the many different application in this time. Different types of ANN will be created, trained and tested the obtained experimental results will be compared and discussed in order to select the best type of ANN, the best ANN architecture which will minimize the error between the targeted function value and the calculated one. |
|
Keywords |
ANN, neuron, FFANN, cascade ANN, Elman ANN, ANN architecture, ANN parameters |
|
URL |
