Training Artificial Neural Network Using Back-Propagation & Particle Swarm Optimization for Image Skin Diseases
Training Artificial Neural Network Using Back-Propagation & Particle Swarm Optimization for Image Skin Diseases

Hanan A. R. Akkar; Samem Abass Salman

Volume 29, Issue 13 , September 2011, , Page 2739-2755

https://doi.org/10.30684/etj.29.13.12

Abstract
  This work is devoted to compression Image Skin Diseases by using Discrete Wavelet Transform (DWT) and training Feed-Forward Neural Networks (FFNN) by using Particle Swarm Optimization(PSO) ...  Read More ...
Training Artificial Neural Networks by PSO to Perform Digital Circuits Using Xilinx FPGA
Training Artificial Neural Networks by PSO to Perform Digital Circuits Using Xilinx FPGA

Hanan A. R. Akkar; Firas R. Mahdi

Volume 29, Issue 7 , May 2011, , Page 1329-1344

https://doi.org/10.30684/ etj.29.7.8

Abstract
  One of the major constraints on hardware implementations of Artificial Neural Networks (ANNs) is the amount of circuitry required to perform the multiplication process of each input ...  Read More ...
Integrating Neural Network With Genetic Algorithms For The Classification Plant Disease
Integrating Neural Network With Genetic Algorithms For The Classification Plant Disease

Alia Karim Abdul Hassan; Sarah Sadoon Jasim

Volume 28, Issue 4 , February 2010, , Page 686-701

https://doi.org/10.30684/etj.28.4.5

Abstract
  In this work Aِِrtificial Neural Network (ANN) is used as a classifier capable ofrecognizing the most important features of the plant disease, with minimum errorvalue. Genetic algorithm ...  Read More ...
Transmission System On –Line Fault Location Using ArtificialNeural Network
Transmission System On –Line Fault Location Using ArtificialNeural Network

Adil Hameed Ahmed; Hatim Ghadhban Abood

Volume 28, Issue 5 , February 2010, , Page 964-979

https://doi.org/10.30684/etj.28.5.9

Abstract
  In this work, protection systems for overhead transmission lines areinvestigated and an efficient technique for on –line fault location based onArtificial Neural Network(ANN ) ...  Read More ...
Artificial Neural Networks Analysis of Treatment Process of Gypseous Soils
Artificial Neural Networks Analysis of Treatment Process of Gypseous Soils

Mohammad M. Al-Ani; Mohammad Y. Fattah; Mahmoud T. A. Al-Lamy

Volume 27, Issue 9 , June 2009, , Page 1811-1832

https://doi.org/10.30684/etj.27.9.13

Abstract
  Artificial Neural Networks (ANNs) are used to relate the properties of gypseous soilsand evaluate the values of compression of soils under different conditions. Therefore, onelayerperception ...  Read More ...
Artificial Neural NetworkModel for Predicting Nonlinear Response of Uniformly Loaded Fixed Plates
Artificial Neural NetworkModel for Predicting Nonlinear Response of Uniformly Loaded Fixed Plates

Ayad Amjad Abdul-Razzak

Volume 25, Issue 3 , May 2007, , Page 334-348

https://doi.org/10.30684/etj.25.3.5

Abstract
  An artificial neural network (ANN) model has been developed for theprediction of nonlinear response for plates with built-in edges and differentsizes, thickness and uniform loads. The ...  Read More ...