Title :
A Java application for the selection of a weights file for a two hidden layers feed forward neural network
Author :
Ene, Alexandru ; Stirbu, Cosmin
Author_Institution :
Univ. of Pitesti, Pitesti, Romania
Abstract :
In this paper we describe the way in which we select the weights set for a two hidden layers feed forward neural network. The weights are selected based on the fault tolerance of the neural network. We developed a Java application for training the network that generates more valid weights files and then the application selects the file that offers the maximum fault tolerance to the faults of the hidden neurons.
Keywords :
Java; feedforward neural nets; Java application; fault tolerance; hidden layers feed forward neural network; hidden neurons; weights file selection; weights files; Artificial neural networks; Biological neural networks; Circuit faults; Fault tolerance; Fault tolerant systems; Feeds; Neurons; fault neurons; the selection of a weights file; two hidden layers feed forward neural network;
Conference_Titel :
Electronics, Computers and Artificial Intelligence (ECAI), 2014 6th International Conference on
Print_ISBN :
978-1-4799-5478-0
DOI :
10.1109/ECAI.2014.7090171
