Preferred Language
Articles
/
bsj-3187
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
...Show More Authors

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

                                 

Scopus Clarivate Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
...Show More Authors

View Publication
Scopus (12)
Crossref (7)
Scopus Clarivate Crossref
Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
solving linear fractional programming problems (LFP) by Using denominator function restriction method and compare it with linear transformations method
...Show More Authors

 

Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
...Show More Authors

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

... Show More
View Publication Preview PDF
Scopus (31)
Crossref (14)
Scopus Crossref
Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
...Show More Authors

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

... Show More
View Publication Preview PDF
Publication Date
Mon Jan 01 2024
Journal Name
Itm Web Of Conferences
Embedded Neural Network like PID Water Heating Controller Implementing Cycle by Cycle Power Control Scheme
...Show More Authors

This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics

... Show More
View Publication
Crossref
Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
...Show More Authors

Scopus (18)
Crossref (11)
Scopus Clarivate Crossref
Publication Date
Mon Jan 02 2012
Journal Name
Journal Of Engineering
3-D Object Recognition using Multi-Wavelet and Neural Network
...Show More Authors

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

... Show More
View Publication
Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
...Show More Authors

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Pose Invariant Palm Vein Identification System using Convolutional Neural Network
...Show More Authors

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

... Show More
View Publication Preview PDF
Scopus (24)
Crossref (2)
Scopus Crossref
Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
...Show More Authors

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

... Show More
Scopus (12)
Crossref (12)
Scopus Clarivate Crossref