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Solving Job-Shop Scheduling Problem Using Genetic Algorithm Approach

Publication Date
Wed Mar 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Genetic –Based Face Retrieval Using Statistical Features

Content-based image retrieval has been keenly developed in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval becomes one of the liveliest researches in the past few years. In a given set of objects, the retrieval of information suggests solutions to search for those in response to a particular description. The set of objects which can be considered are documents, images, videos, or sounds. This paper proposes a method to retrieve a multi-view face from a large face database according to color and texture attributes. Some of the features used for retrieval are color attributes such as the mean, the variance, and the color image's bitmap. In add

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Publication Date
Sun May 17 2020
Journal Name
Iraqi Journal Of Science
Solving Fuzzy Differential Equations by Using Power Series

In this paper, the series solution is applied to solve third order fuzzy differential equations with a fuzzy initial value. The proposed method applies Taylor expansion in solving the system and the approximate solution of the problem which is calculated in the form of a rapid convergent series; some definitions and theorems are reviewed as a basis in solving fuzzy differential equations. An example is applied to illustrate the proposed technical accuracy. Also, a comparison between the obtained results is made, in addition to the application of the crisp solution, when the-level equals one.

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving Oscillating Problems Using Modifying Runge-Kutta Methods

     This paper develop conventional Runge-Kutta methods of order four and order five to solve ordinary differential equations with oscillating solutions. The new modified Runge-Kutta methods (MRK) contain the invalidation of phase lag, phase lag’s derivatives, and amplification error. Numerical tests from their outcomes show the robustness and competence of the new methods compared to the well-known Runge-Kutta methods in the scientific literature.

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Solving Fuzzy Games Problems by Using Ranking Functions

In this paper, we deal with games of fuzzy payoffs problem while there is uncertainty in data. We use the trapezoidal membership function to transform the data into fuzzy numbers and utilize the three different ranking function algorithms. Then we compare between these three ranking algorithms by using trapezoidal fuzzy numbers for the decision maker to get the best gains

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
Reducing Lost Circulation Problem by Using Rice Material

Drilling fluid loss during drilling operation is undesirable, expensive and potentially hazardous problem.

    Nasiriyah oil field is one of the Iraqi oil field that suffer from lost circulation problem. It is known that Dammam, um-Radoma, Tayarat, Shiranish and Hartha are the detecting layers of loss circulation problem. Different type of loss circulation materials (LCMs) ranging from granular, flakes and fibrous were used previously to treat this problem.  

    This study presents the application of rice as a lost circulation material that used to mitigate and stop the loss problem when partial or total losses occurred.

     The experim

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Publication Date
Thu Feb 28 2019
Journal Name
Iraqi Journal Of Science
Skin Detection using Improved ID3 Algorithm

Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Branch and Bound Algorithm with Penalty Function Method for solving Non-linear Bi-level programming with application

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

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Publication Date
Fri Jan 01 2016
Journal Name
Wuhaib, K.m. , Hadi, B.h. , Hassan, W.a. Iraqi Journal Of Agricultural Sciences, 2016, 47(5), Pp. 1151–1165
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Using Semi-Analytic Technique for Solving Lane Emden Equations

This paper propose the semi - analytic technique using two point osculatory interpolation to construct polynomial solution for solving some well-known classes of Lane-Emden type equations which are linear ordinary differential equations, and disusse the behavior of the solution in the neighborhood of the singular points along with its numerical approximation. Many examples are presented to demonstrate the applicability and efficiency of the methods. Finally , we discuss behavior of the solution in the neighborhood of the singularity point which appears to perform satisfactorily for singular problems.

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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