scholarly journals A robust behavior of Feed Forward Back propagation algorithm of Artificial Neural Networks in the application of vertical electrical sounding data inversion

2012 ◽  
Vol 3 (5) ◽  
pp. 729-736 ◽  
Author(s):  
Y. Srinivas ◽  
A. Stanley Raj ◽  
D. Hudson Oliver ◽  
D. Muthuraj ◽  
N. Chandrasekar
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Back Propagation ◽  
Vertical Electrical Sounding ◽  
Back Propagation Algorithm ◽  
Feed Forward ◽  
Data Inversion ◽  
Feed Forward Back Propagation ◽  
Propagation Algorithm ◽  
Electrical Sounding

Artificial neural networks back propagation algorithm for cutting force components predictions

2013 ◽  
Vol 14 (6) ◽  
pp. 431-439 ◽  
Author(s):  
Issam Hanafi ◽  
Francisco Mata Cabrera ◽  
Abdellatif Khamlichi ◽  
Ignacio Garrido ◽  
José Tejero Manzanares
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Cutting Force ◽  
Back Propagation ◽  
Back Propagation Algorithm ◽  
Propagation Algorithm ◽  
Cutting Force Components ◽  
Artificial Neural ◽  
Force Components

ALGORITMA PROPAGASI BALIK DALAM PENCARIAN POLA TRAINING TERBAIK UNTUK MENENTUKAN PREDIKSI PRODUKSI USAHA SONGKET SILUNGKANG DENGAN MENGGUNAKAN MATLAB

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Rima Liana Gema ◽  
Devia Kartika
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Artificial Neural Networks ◽  
Back Propagation ◽  
Back Propagation Algorithm ◽  
Backpropagation Algorithm ◽  
Propagation Algorithm ◽  
Testing Stage ◽  
West Sumatra

One method used in Artificial Neural Networks is a backpropagation algorithm that is widely used in predicting and pattern recognition. Songket is one of the works of skilled hands of the original Silungkang craftsmen, Sawahlunto City, West Sumatra who have varied and unique patterns and motifs. This study uses a back propagation algorithm to find the best training pattern to facilitate the determination of the production prediction of Silungkang songket business using the Matlab application. The best training patterns obtained are expected to be used in data processing at the testing stage in order to obtain predictions for the production of songket business for the future. Keywords: production, songket, back propagation.

scholarly journals On Training Of Feed Forward Neural Networks

2007 ◽  
Vol 4 (1) ◽  
pp. 158-164
Author(s):  
Baghdad Science Journal
Keyword(s):  
Neural Networks ◽  
Back Propagation ◽  
Training Algorithms ◽  
Back Propagation Algorithm ◽  
Performance Function ◽  
Feed Forward ◽  
Global Properties ◽  
Propagation Algorithm ◽  
Feed Forward Neural Networks ◽  
And Storage

In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

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