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Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the study showed the efficiency of neural network in application which represented less distance and smaller determinant matrix of  variance covariance compared with sample of Fast – MCD – Nested Extension .                                                                                                

As for practical side has been 9 kinds of chemical and physical indicators for water pollution, the research covered all the provinces of Iraq except Kardistan region and ten month of the year in 2013 and sample size of 898 .

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
Optimizing genetic prediction: Define-by-run DL approach in DNA sequencing
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Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

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Publication Date
Sun Dec 01 2019
Journal Name
Indian Journal Of Ecology
Evaluation of maize hybrids, their inbred lines and estimation of genetic divergence based on cluster analysis
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sci.
Evaluating the performance of introduced varieties of Maize (Zea mays L.) And estimating some genetic parameters
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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Statistical
Evaluating the performance of introduced varieties of maize (Zea Mays L.) and estimating some genetic parameters
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Publication Date
Fri Mar 01 2019
Journal Name
Iraqi Journal Of Physics
The dispersion in spherical statistical optical potential (SOM) from the interaction of fast neutrons with197Au nucle
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A statistical optical potential has been used to analyze and
evaluate the neutron interaction with heavy nuclei 197Au at the
neutron energy range (1-20 MeV). Empirical formulae of the optical
potentials parameters are predicted by using ABAREX Code with
minimize accuracy compared with experimental bench work data.
The total elastic, absorption, shape elastic and total compound crosssections are calculated for different target nuclei and different
incident neutron energies to predict the appropriate optical
parameters that suit the present interaction. Also the dispersion
relation linking between real and imaginary potential is analyzed
with more accuracy. The results indicate the behavior of the
dispersion c

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Publication Date
Fri Jun 05 2026
Journal Name
Al–bahith Al–a'alami
New Methods and Old Issues: Theoretical and Methodological Approaches to Social Network Sites in the Arab Region
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This paper critically looks at the studies that investigated the Social Network Sites in the Arab region asking whether they made a practical addition to the field of information and communication sciences or not. The study tried to lift the ambiguity of the variety of names, as well as the most important theoretical and methodological approaches used by these studies highlighting its scientific limitations. The research discussed the most important concepts used by these studies such as Interactivity, Citizen Journalism, Public Sphere, and Social Capital and showed the problems of using them because each concept comes out of a specific view to these websites. The importation of these concepts from a cultural and social context to an Ara

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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Publication Date
Fri May 01 2026
Journal Name
Retos
Using artificial neural networks to assign soccer players by physical and motor abilities
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Introduction: The introduction of analytics tools in sports indicates that artificial neural networks can be one of the intelligent approaches to process complex data and identify patterns that help players move according to their most suitable positions. Objective: The purpose of this research is to investigate the possibility of using artificial neural networks to determine the physical and motor abilities of football players and determine their suitable playing positions based on exact quantitative indicators. Method: The study sample consists of 45 youth players aged (15–16) years from the Espanyol Football Academy in Baghdad. The results are analyzed using a multilayer perceptron (MLP) artificial neural network model to ident

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Publication Date
Sun Mar 01 2015
Journal Name
Computer Systems Science & Engineering
Parameters' fine tuning of differential evolution algorithm
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Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of par

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