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Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
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       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.

                                 

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Publication Date
Tue Nov 09 2021
Journal Name
Abu Dhabi International Petroleum Exhibition & Conference
Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
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Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit</p> ... Show More
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Publication Date
Thu Apr 03 2025
Journal Name
Isa Transactions
Optimal hybrid type-3 fuzzy controller for horizontal axis wind turbines: Comparative study
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The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six differen

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The impact of empowerment strategies on the characteristics of work enrichment An exploratory research to the views of a sample of the leaders of the Ministry of Oil in Iraq
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The study aimed to investigate the relationship between empowerment strategies and their impact on the success of enrichment work, it included the dimensions of empowerment strategies (power, knowledge, information, rewards), The dimensions of Job enrichment are (Skill variety, Task identity, Task significance, Autonomy, Feedback). The study was conducted at the headquarters of the Iraqi Oil Ministry in Baghdad and was based on a sample of the leadership of the ministry of managers consisting of 215 people. The data were collected using the questionnaire method based on scientific standards adopted in previous st

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The use of the Biz method and classical methods in estimating the parameters of the binary logistic regression model
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Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
مقارنة مقدر بيز مع طريقة الامكان الاعظم لتقدير معلمتي معكوس التوزيع الاسي المعمم في حالة ضبابية البيانات
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In this paper, the generalized inverted exponential distribution is considered as one of the most important distributions in studying failure times. A shape and scale parameters of the distribution have been estimated after removing the fuzziness that characterizes its data because they are triangular fuzzy numbers. To convert the fuzzy data to crisp data the researcher has used the centroid method. Hence the studied distribution has two parameters which show a difficulty in separating and estimating them directly of the MLE method. The Newton-Raphson method has been used.

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
The relationship between organizational justice and empowerment and their impact on achieving organizational commitment (field study in the Department of Labor and Vocational Training)
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The research has deal with the relationship between organizational justice and empowerment and their impact on the achievement of organizational commitment in the office of Labour and Vocational Training. To study the research problem which is represented a sense that employees with low levels of organizational justice and empowerment and the reflection on the organizational commitment of the employees, so that Has been collecting data and information relating to research by designing a questionnaire, were distributed to a sample of (50) people in the office mentioned, and the results of the study to confirm the research hypotheses. and the key results of the research was the presence of correlation relationships and the effect o

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Mon Sep 01 2025
Journal Name
International Journal Of Renewable Energy Research
A Comparative Study of Optimal Fuzzy Logic Controllers for Blade Pitch Angle in Horizontal-axis Wind Turbines
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The blade pitch angle (BPA) in wind turbine (WT) is controlled to maximize output power generation above the rated wind speed (WS). In this paper, four types of controllers are suggested and compared for BPA controller in WT: PID controller (PIDC), type-1 fuzzy logic controller (T1-FLC), type-2 fuzzy logic controller (T2-FLC), and hybrid fuzzy-PID controller (FPIDC). The Mamdani and Sugeno fuzzy inference systems (FIS) have been compared to find the best inference system used in FLC. Genetic algorithm (GA) and Particle swarm optimization algorithm (PSO) are used to find the optimal tuning of the PID parameter. The results of500-kw horizontal-axis wind turbine show that PIDC based on PSO can reduced 2.81% in summation error of power

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Publication Date
Tue Dec 09 2025
Journal Name
Journal Of Al-farahidi’s Arts
Artificial Intelligence Applications in Machine Translation and Their Role in Bridging Semantic Gaps Across Languages: A Comparative Analytical Study of Chat GPT and Deep Seek
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With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type
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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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