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On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
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The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

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Publication Date
Fri Sep 01 2017
Journal Name
2017 9th Computer Science And Electronic Engineering (ceec)
Modelling the power cost and trade-off of live migration the virtual machines in cloud-radio access networks
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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Wed Oct 28 2015
Journal Name
Journal Of Mathematics And System Science
Simulating Particle Swarm Optimization Algorithm to Estimate Likelihood Function of ARMA(1, 1) Model
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Publication Date
Wed Mar 01 2017
Journal Name
International Journal Of Cardiology
The role of myocardial performance index in assessment of left ventricular function in patients with valvular mitral regurgitation
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Background: Mitral regurgitation (MR) is the most commonly encountered valve lesion in modern clinical practice. Severe mitral regurgitation may cause systolic dysfunction. Left ventricular ejection fraction may not be an accurate measurement of LV function in patients with mitral insufficiency. Myocardial performance index (MPI) is a simple non invasive measure of myocardial function. Methods: The study involved 50 patients with valvular mitral regurgitation and 50 healthy subjects as a control group. Transthoracic echocardiography was carried out for all patients and control group. The echocardiographic measurements included left ventricular end diastolic and end systolic dimensions, left atrial diameter, ejection fraction (EF), and myoca

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Publication Date
Wed Sep 15 2021
Journal Name
2021 International Conference On Computing And Communications Applications And Technologies (i3cat)
Parallel Hybrid String Matching Algorithm Using CUDA API Function
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Publication Date
Thu Sep 15 2022
Journal Name
Journal Of Mechanical Engineering
Thermal Buckling of Laminated Plates using Modified Mantari Function
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Critical buckling temperature of laminated plate under thermal load varied linearly along the thickness, is developed using a higher-order shape function which depends on a parameter ‘‘m’’, which is improved to obtain results for thin and thick plates. Laminated plates’ equations of motion are obtained using virtual work principle and solved for simply supported boundary conditions. Angle and cross laminates thermal buckled mode shapes with different E1/E2 proportion, number of plies, (α2/α1) proportion, aspect ratios, are investigated. It is observed that this shape function gives thermal buckling for thin and thick plates but with m = 0.05 that agree well with other theories and linear distribution of temperature giv

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
NONPARAMETRIC And Semiparametric Bayesian Estimators in survival function analysis
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 Most statistical research generally relies on the study of the behaviour of different phenomena during specific time periods and the use of the results of these studies in the development of appropriate recommendations and decision-making and for the purpose of statistical inference on the parameters of the statistical distribution of life times in  The technical staff of most of the manufacturers in the research units of these companies deals with censored data, the main objective of the study of survival is the need to provide information that is the basis for decision making and must clarify the problem and then the goals and limitations of this study and that  It may have different possibilities to perform the

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Software Protection by Combining Hash Function with Hardware Identifications
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This paper presents a hybrid software copy protection scheme, the scheme is applied to
prevent illegal copying of software by produce a license key which is unique and easy to
generate. This work employs the uniqueness of identification of hard disk in personal
computer which can get by software to create a license key after treated with SHA-1 one way
hash function. Two mean measures are used to evaluate the proposed method, complexity
and processing time, SHA-1 can insure the high complexity to deny the hackers for produce
unauthorized copies, many experiments have been executed using different sizes of software
to calculate the consuming time. The measures show high complexity and short execution
time for propos

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
comparison between the methods estimate nonparametric and semiparametric transfer function model in time series the Using simulation
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 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

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