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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
Mon Dec 04 2017
Journal Name
Al-qadisiyah Journal For Administrative And Economic Sciences
Survival Function Estimating of Single age Groups for Generalized Gamma Distribution with Simulation.
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The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the

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Publication Date
Sat Nov 01 2014
Journal Name
International Journal Of Basic And Applied Sciences
A reliable iterative method for solving the epidemic model and the prey and predator problems
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In the present article, we implement the new iterative method proposed by Daftardar-Gejji and Jafari (NIM) [V. Daftardar-Gejji, H. Jafari, An iterative method for solving nonlinear functional equations, J. Math. Anal. Appl. 316 (2006) 753-763] to solve two problems; the first one is the problem of spread of a non-fatal disease in a population which is assumed to have constant size over the period of the epidemic, and the other one is the problem of the prey and predator. The results demonstrate that the method has many merits such as being derivative-free, overcome the difficulty arising in calculating Adomian polynomials to handle the nonlinear terms in Adomian Decomposition Method (ADM), does not require to calculate Lagrange multiplier a

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Some properties of finite dimensional fuzzy anti-normed linear spaces
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            In this paper the definition of fuzzy anti-normed linear spaces and its basic properties are used to prove some properties of a finite dimensional fuzzy anti-normed linear space.    

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Properties of Fuzzy Compact Linear Operators on Fuzzy Normed Spaces
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In this paper the definition of fuzzy normed space is recalled and its basic properties. Then the definition of fuzzy compact operator from fuzzy normed space into another fuzzy normed space is introduced after that the proof of an operator is fuzzy compact if and only if the image of any fuzzy bounded sequence contains a convergent subsequence is given. At this point the basic properties of the vector space FC(V,U)of all fuzzy compact linear operators are investigated such as when U is complete and the sequence ( ) of fuzzy compact operators converges to an operator T then T must be fuzzy compact. Furthermore we see that when T is a fuzzy compact operator and S is a fuzzy bounded operator then the composition TS and ST are fuzzy compact

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Publication Date
Sun Apr 03 2016
Journal Name
Journal Of Educational And Psychological Researches
The Level of Computer Literacy of the Students at Al Quds Open University in Tulkarm Branch
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The purpose of this study is to assess the level of computer literacy of the students at AlQuds open university in Tulkarm Branch. The study investigates the effects of the variables of gender, specialization, academic level, owning a personal computer, internet communication, and own an email account on the level of computer literacy. A test of computer literacy was constructed by the researchers consisting of (37) multiple choice items with a reliability rate (0.85). The study population consisted of (4100) students, while the sample contained (352) students. The study revealed that the level of computer literacy of the students at AlQuds Open University in Tulkarm Branch was (66.2 %) which is educationally acceptable. It also

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Publication Date
Thu Feb 15 2024
Journal Name
Evolving Systems
Boosted Aquila Arithmetic Optimization Algorithm for multi-level thresholding image segmentation
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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Four Level Prior Distributions
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Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Mon Jan 01 2018
Journal Name
Proceedings Of The 10th International Joint Conference On Computational Intelligence
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison of Practical Investigations for CO Emissions Emitted From Single Cylinder S. I. Engine Fueled With Different Kinds of Hydrocarbon Fuels and Hydrogen
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Liquefied petroleum gas (LPG), Natural gas (NG) and hydrogen were all used to operate spark ignition internal combustion engine Ricardo E6. A comparison of CO emissions emitted from each case, with emissions emitted from engine fueled with gasoline as a fuel is conducted.

The study was accomplished when engine operated at HUCR for gasoline n(8:1), was compared with its operation at HUCR for each fuel. Compression ratio, equivalence ratio and spark timing were studied at constant speed 1500 rpm.

CO concentrations were little at lean ratios; it appeared to be effected a little with equivalence ratio in this side, at rich side its values became higher, and it appeared to be effected by equivalence ratio highly, the results s

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