Design a System to Estimate the Road Construction Project Preliminary Equipment Requirements in the Design Stage
Design a System to Estimate the Road Construction Project Preliminary Equipment Requirements in the Design Stage

Raid S. Abd Ali; Tareq A. khaleel; Shealan H. Ameen

Volume 34, 13A , December 2016, , Page 554-565

https://doi.org/10.30684/etj.34.13A.20

Abstract
  Road construction projects in Iraq require a developmental study of the planning process toward building computerized management systems. In this thesis, a management system has been ...  Read More ...
Prediction Fatigue Life of Aluminum Alloy 7075 T73 Using Neural Networks and Neuro-Fuzzy Models
Prediction Fatigue Life of Aluminum Alloy 7075 T73 Using Neural Networks and Neuro-Fuzzy Models

Mustafa S. Abdullatef; Nazhat . AlRazzaq; Mustafa M. Hasan

Volume 34, 2A , February 2016, , Page 272-283

https://doi.org/10.30684/etj.2016.112624

Abstract
  In present paper the fatigue life of aluminum alloy 7075 T73 under constant amplitude loading is predicted using ANN and ANFIS models. Many neural networks models are used for this ...  Read More ...
Effect of Some Vegetables (Carrots, Onion, Parsley, and Red radish) on Corrosion Behavior of Amalgam Dental Filling in Artificial Saliva
Effect of Some Vegetables (Carrots, Onion, Parsley, and Red radish) on Corrosion Behavior of Amalgam Dental Filling in Artificial Saliva

Slafa Ismael Ibrahim; Nemir Ahmed Al-Azzawi; Shatha Mizhir Hasan; Hussein H. Karim; Ammar M. M. Al-Qaissi; Ahmed Chyad Kadhim; Mehdi Munshid Shellal; Sinan Majid Abdul Satar; Wahid S. Mohammad; Assad Oda Jassim; Khalid salem Shibib; Karema Assi Hamad; Haqui Ismael Qatta; Hayder Hadi Abbas; Kanaan A. Jalal; Hussain Kassim Ahmad; Makram A. Fakhri; Mohanned M.H. AL-Khafaji; Hussam Lefta Alwan; Baraa M.H. Albaghdadi

Volume 32, Issue 5 , June 2014, , Page 1216-1226

https://doi.org/10.30684/etj.32.5A.11

Abstract
  This work involves study corrosion behavior of amalgam in presence of some vegetables including (Carrots, Onion, Parsley, and Red radish) which were chosen because they require mastication ...  Read More ...
Roughness Assessment for Machined Surfaces in Turning Operation Using Neural Network
Roughness Assessment for Machined Surfaces in Turning Operation Using Neural Network

Mohanned M.H. AL-Khafaji; Hussam Lefta Alwan; Baraa M.H. Albaghdadi

Volume 32, Issue 5 , June 2014, , Page 1331-1343

https://doi.org/10.30684/etj.32.5A.20

Abstract
  Feed forward artificial neural network has been applied to predict the quality of turned surfaces for two types of coated carbide inserts. Four networks were proposed for each insert. ...  Read More ...
Control on 3-D Fixable Wing Flutter Using an Adaptive Neural Controller
Control on 3-D Fixable Wing Flutter Using an Adaptive Neural Controller

Mauwafak Ali Tawfik; Mohammed Idris Abu-Tabikh; Hayder Sabah Abd Al-Amir

Volume 30, Issue 16 , September 2012, , Page 2858-2874

https://doi.org/10.30684/etj.30.16.9

Abstract
  An adaptive neural controller to control on flutter in 3-D flexible wing is proposed. The aeroelastic model was based on the coupling between structure-of the equivalent plate (wing) ...  Read More ...
A Hybrid Neural Based Dynamic Branch Prediction Unit
A Hybrid Neural Based Dynamic Branch Prediction Unit

Gheni A. Ali

Volume 30, Issue 6 , March 2012, , Page 1066-1081

https://doi.org/10.30684/etj.30.6 12

Abstract
  Modern high performance processor architectures have come to depend upon highly pipelined operation in order to achieve improvements in operating speed. As a result, the cost associated ...  Read More ...
Intrusion Detection and Attack Classifier Based on Three Techniques: A Comparative Study
Intrusion Detection and Attack Classifier Based on Three Techniques: A Comparative Study

Adel Sabry Issa; Adnan Mohsin Abdulazeez Brifcani

Volume 29, Issue 2 , January 2011, , Page 386-412

https://doi.org/10.30684/etj.29.2.17

Abstract
  Different soft-computing based methods have been proposed in recent years for the development of intrusion detection systems. The purpose of this work is to development, implement and ...  Read More ...
Optimizing Opto-Electronic Cellular Neural Networks Using Bees Swarm Intelligent
Optimizing Opto-Electronic Cellular Neural Networks Using Bees Swarm Intelligent

Hanan A.R.Akkar

Volume 28, Issue 21 , October 2010, , Page 6237-6252

https://doi.org/10.30684/etj.28.21.3

Abstract
  This paper presents an application of Bees algorithm to the optimization of cellular neural network for opto-electronics design, where cellular neural networks bees are a large – ...  Read More ...
Design of a Neural Networks Linearization for Temperature Measurement System Based on Different Thermocouples Sensors Types
Design of a Neural Networks Linearization for Temperature Measurement System Based on Different Thermocouples Sensors Types

Ahmed Sabah Abdul Ameer Al-Araji

Volume 27, Issue 8 , June 2009, , Page 1622-1639

https://doi.org/10.30684/etj.27.8.16

Abstract
  This paper describes an experimental method for the estimation of nonlinearity,calibration and testing of the different types of thermocouples (J and K) using modifiedElman recurrent ...  Read More ...
Offline Signature Recognition and Verification Based on Artifical Neural Network
Offline Signature Recognition and Verification Based on Artifical Neural Network

Mohammed A. Abdala; Noor Ayad Yousif

Volume 27, Issue 7 , May 2009, , Page 1376-1384

https://doi.org/10.30684/etj.27.7.13

Abstract
  In this paper, a problem for Offline Signature Recognition and Verification is presented. Asystem is designed based on two neural networks classifier and three powerful features (global,texture ...  Read More ...
Study of Principle Component Analysis and Learning Vector Quantization Genetic Neural Networks
Study of Principle Component Analysis and Learning Vector Quantization Genetic Neural Networks

Mazin Z. Othman; Arif A. Al-Qassar

Volume 27, Issue 2 , January 2009, , Page 321-331

https://doi.org/10.30684/etj.27.2.10

Abstract
  In this work, the Genetic Algorithm (GA) is used to improve the performance ofLearning Vector Quantization Neural Network (LVQ-NN), simulation results show thatthe GA algorithm works ...  Read More ...
Feedforward Controller for Nonlinear Systems Utilizing a Genetically Trained Fuzzy Neural Network
Feedforward Controller for Nonlinear Systems Utilizing a Genetically Trained Fuzzy Neural Network

Omar F. Lutfy Al-Karkhy

Volume 25, Issue 3 , May 2007, , Page 475-494

https://doi.org/10.30684/etj.25.3.19

Abstract
  This paper presents an intelligent controller that acts as a FeedForwardController (FFC). utilizing the benefits of Fuzzy Logic (FL), Neural Networks(NNs) and Genetic Algorithms (GAs), ...  Read More ...