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Efficient design of neural network based on modified LM training algorithm for solving nonlinear 4th order 3D-PDEs 
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Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testing is vast and the number of faults corrected by bug fixing changes only insignificantly. The suggested design addressing minimization problems employs a feed-forward approach to solve problems like these equations by converting the original problem into an optimization. Efficient design is achieved through a calculated parameter for learning with high precision. To clarify applicability, reliability, and accuracy for this design, some examples are provided. Additionally, to demonstrate the efficiency of the proposed design, comparisons were conducted with other designs.

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Publication Date
Mon Dec 04 2023
Journal Name
Aip Conf. Proc
Double LA-transform and their properties for solving partial differential equations
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Scopus
Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A Proposed Analytical Method for Solving Fuzzy Linear Initial Value Problems
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     In this article, we aim to define a universal set consisting of the subscripts of the fuzzy differential equation (5) except the two elements  and , subsets of that universal set are defined according to certain conditions. Then, we use the constructed universal set with its subsets for suggesting an analytical method which facilitates solving fuzzy initial value problems of any order by using the strongly generalized H-differentiability. Also, valid sets with graphs for solutions of fuzzy initial value problems of higher orders are found.

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Publication Date
Thu May 30 2024
Journal Name
Journal Of Interdisciplinary Mathematics
Laplace transform-adomian decomposition approach for solving random partial differential equations
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Market share is a major indication of business success. Understanding the impact of numerous economic factors on market share is critical to a company’s success. In this study, we examine the market shares of two manufacturers in a duopoly economy and present an optimal pricing approach for increasing a company’s market share. We create two numerical models based on ordinary differential equations to investigate market success. The first model takes into account quantity demand and investment in R&D, whereas the second model investigates a more realistic relationship between quantity demand and pricing.

Scopus (2)
Scopus
Publication Date
Thu Jan 04 2018
Journal Name
Journal Of Electrical Engineering And Technology
An efficient selective method for audio watermarking against de-synchronization attacks
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Scopus (9)
Scopus
Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Human Sport And Exercise - 2019 - Spring Conferences Of Sports Science
The effect of special force training on the development of biomechanical variables for running raising awareness during the performance on the jumping table
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Publication Date
Wed Jun 01 2016
Journal Name
International Educational Scientific Research Journal
EFFICIENTMETHODSOFIRISRECOGNITION
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Identification by biological features gets tremendous importance with the increasing of security systems in society. Various types of biometrics like face, finger, iris, retina, voice, palm print, ear and hand geometry, in all these characteristics, iris recognition gaining attention because iris of every person is unique, it never changes during human lifetime and highly protected against damage. This unique feature shows that iris can be good security measure. Iris recognition system listed as a high confidence biometric identification system; mostly it is divide into four steps: Acquisition, localization, segmentation and normalization. This work will review various Iris Recognition systems used by different researchers for each recognit

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Publication Date
Mon Feb 23 2026
Journal Name
Al-fatih Journal
A comparative study of resistance training on land and in the aqueousTo develop some capacity for three Al Wathba
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أن التطور العلمي الحاصل فيما يخص المجال الرياضي أرسى آفاق جديدة لمواكبة التطور الكبير في مجا ل الألعاب والفعاليات الرياضية المختلفة ,و أن تحقيق النتائج الجيدة في فعاليات العاب القوى بشكل عام والثلاثية بشكل خاص في التدريب الرياضي يتطلب إتباع الأساليب العلمية الدقيقة والموضوعية بشكل سليم ومخطط له،فضلا عنة تطبيق نظريات ومنحى جديد لمواكبة الاتجاهات الحديثة في تحقيق النتائج الجيدة للوصول إلى المستويات العالية

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Publication Date
Fri Jul 07 2017
Journal Name
International Journal Of Science And Research (ijsr)
Automatic brain tumor segmentation from MRI Images using superpixels based split and Merge algorithm
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RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2

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Publication Date
Tue Jun 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Application of Neural Network in the Identification of the Cumulative Production from AB unit in Main pays Reservoir of South Rumaila Oil Field.
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A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

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