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jeasiq-1893
Comparison Branch and Bound Algorithm with Penalty Function Method for solving Non-linear Bi-level programming with application
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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
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Determination Optimum Inventory Level for Material Using Genetic Algorithm
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The integration of decision-making will lead to the robust of its decisions, and then determination optimum inventory level to the required materials to produce and reduce the total cost by the cooperation of purchasing department with inventory department and also with other company,s departments. Two models are suggested to determine Optimum Inventory Level (OIL), the first model (OIL-model 1) assumed that the inventory level for materials quantities equal to the required materials, while the second model (OIL-model 2) assumed that the inventory level for materials quantities more than the required materials for the next period.             &nb

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Several Nonlinear Estimators for Regression Function
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The aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.

 Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.

We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).

The results proved that the (ANN) estimator is the best nonlinear estimator am

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Publication Date
Sun Jun 27 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Mothers’ Knowledge about Their Children with Sickle Cell Anemia and Non-Pharmacological Approaches to Pain Management in Basra Center for Hereditary Blood Diseases
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Objective(s): To assess mothers’ knowledge about their children with sickle cell anemia and non-Pharmacological approaches to pain management and found some relationship between mothers knowledge and their demographic data of age, level of education, and occupation.
Methodology: A descriptive design used in the present study established was for a period from September 19th, 2020 to March 30th, 2021. The study was conducted on a non-probability (purposive) sample of (30) mother their children with sickle cell anemia was chosen. The data were analyzed through the application of descriptive and inferential statistical approaches which are applied by using SPSS version 22.0.
Results: The findings of the study indicated that moderate

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Publication Date
Thu Jan 01 2026
Journal Name
Aip Conference Proceedings
Using gravitational search algorithm for solving optimization problems based on hypervolume indicator
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Extended utilization of adaptive algorithms, Evaluative Algorithms (EAs), to address these issues offers a way to handle massive multi-objective optimization, even if the algorithmic method for handling combinations of objectives (CO) has been accessible for quite some time. Combining the idea of superiority with the Hypervolume (HV) tag approach, the GSA algorithm utilizes various target effects to explain several algorithms depending on the Hypervolume (HV) spacing. The Multi-objective Gravitational Search Algorithm with Hypervolume (MOGSA/HV). Since rapid convergence could result from GSA foundation work, Hypervolume rewrites the multi-objective problem (MOP) as a sequence of Tchebycheff solutions, improving it. Since the one in charge h

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Publication Date
Sun Jan 01 2006
Journal Name
Journal Of Engineering
SELF ORGANIZING FUZZY CONTROLLER FOR A NON-LINEAR TIME VARYING SYSTEM
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This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.

Publication Date
Sun Jul 04 2021
Journal Name
(al-qadisiyah-journal Of Pure Science(qjps
Reliable Iterative Method for solving Volterra - Fredholm Integro Differential Equations
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The aim of this paper is to propose a reliable iterative method for resolving many types of Volterra - Fredholm Integro - Differential Equations of the second kind with initial conditions. The series solutions of the problems under consideration are obtained by means of the iterative method. Four various problems are resolved with high accuracy to make evident the enforcement of the iterative method on such type of integro differential equations. Results were compared with the exact solution which exhibits that this technique was compatible with the right solutions, simple, effective and easy for solving such problems. To evaluate the results in an iterative process the MATLAB is used as a math program for the calculations.

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Publication Date
Fri Jan 01 2016
Journal Name
Results In Physics
An efficient iterative method for solving the Fokker–Planck equation
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Publication Date
Tue Jan 02 2018
Journal Name
Arab Journal Of Basic And Applied Sciences
Daftardar-Jafari method for solving nonlinear thin film flow problem
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Publication Date
Tue Sep 30 2014
Journal Name
Iosr Journal Of Mathematics
Modification Adomian Decomposition Method for solving Seventh OrderIntegro-Differential Equations
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In this paper, a method based on modified adomian decomposition method for solving Seventh order integro-differential equations (MADM). The distinctive feature of the method is that it can be used to find the analytic solution without transformation of boundary value problems. To test the efficiency of the method presented two examples are solved by proposed method.

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