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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
Mon Jan 01 2024
Journal Name
Communications In Computer And Information Science
Enhancing the Performance of Wireless Body Area Network Routing Protocols Based on Collaboratively Evaluated Values
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Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i

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Publication Date
Wed Oct 17 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
ESTIMATION OF MUNICIPAL SOLID WASTE GENERATION AND LANDFILL VOLUME GENERATION AND LANDFILL VOLUME USING ARTIFICIAL NEURAL NETWORKS
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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Improving the Durability of Streak and Thermal Insulation of Petroleum Pipes by Using Polymeric Based Paint System: Polymer Matrix Composites have several and wide applications
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This research deals with increasing the hardening and insulating the petroleum pipes against the conditions and erosion of different environments. So, basic material of epoxy has been mixed with Ceramic Nano Zirconia reinforcement material 35 nm with the percentages  (0,1,2,3,4,5) %, whereas the paint basis of broken petroleum pipes was used  to paint on it, then it was cut into dimensions (2 cm. × 2 cm.) and 0.3cm high. After the paint and percentages are completed, the samples were immersed into the paint. Then, the micro-hardness was checked according to Vickers method and thermal inspection of paint, which contained (Thermal conduction, thermal flux and Thermal diffusivity), the density of the painted samples was calculate

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Publication Date
Sun Jun 30 2024
Journal Name
Sports Culture
Designing and rationing of test to measure the motor compatibility for the eye and the leg for students of the Faculty of Physical Education and Sports Sciences, Samarra University
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The research aims to identify: 1-Designing a test to measure the movement compatibility of the eye and the leg for the students of the Faculty of Physical Education and Sports Sciences, Samarra University. 2-Codification (setting scores and standard levels) for the results of the motor compatibility test for the eye and the leg for students of the Faculty of Physical Education and Sports Sciences, Samarra University. The researchers reached the some following conclusions: 1-A test to measure the movement compatibility of the eye and the leg for the students of the Faculty of Physical Education and Sports Sciences. 2-There is a discrepancy in the standard levels of the research sample.

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Publication Date
Sun Mar 01 2015
Journal Name
Baghdad Science Journal
Synthesis of Mixed Ligand Complexes of M(II) Dithiocarbamato Derivative and 2,2'-bipyridyl and Study their Cytotoxic Effect Against HepG2 Cell Line in vitro
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Mixed ligand of Co and Ni (II) complexes were prepared from [5-(p-nitrophenyl)-4/-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide](TRZ.DTC) as primary ligand and 2,2'-bipyridyl (bipy) as a co-ligand with metal salts. These complexes were analytically and spectroscopically characterized in solid state by elemental analyses, flame atomic absorption, magnetic susceptibility and molar conductance measurements, as well as by UV–Vis and FTIR spectroscopy. Infrared, ultra violet spectra reveal a bidentate coordination of the two ligands with metal ions 1:1:1 mole ratio. Room temperature magnetic moments and solid reflectance spectra data indicate paramagnetic complexes with five-coordinate square pyramidal geometry for nickel (II) comple

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Publication Date
Mon May 25 2015
Journal Name
International Journal Of Current Research
Synthesis, Spectral and Antimicrobial Activity of Mixed Ligand Complexes of Co(II),Ni(II),Cu(II) and Zn(II) with 4-aminoantipyrine and Tributylphosphine
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Complexes of Co(II),Ni(II),Cu(II)and Zn(II) with mixed ligand of 4- aminoantipyrine (4-AAP) and tributylphosphine (PBu3) were prepared in aqueous ethanol with (1:2:2) (M:L:PBu3). The prepared complexes were characterized using flame atomic absorption, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition biological activity of the two ligands and their complexes against three selected type of bacteria were also examined. The general compositions of the complexes are found to be [M(4-AAP)2(PBu3)2] Cl2 . Where M= Co(II),Ni(II),Cu(II)and Zn(II). Some of the complexes exhibit good bacterial activities. From the obtained data the octahedral structures have suggested for all prepare

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
q-Difference Equation for the Operator E ̃(x,a;θ) and their Applications for the Polynomials h_n (a,b,x|q^(-1))
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This paper concentrates on employing the -difference equations approach to prove another generating function, extended generating function, Rogers formula and Mehler’s formula for the polynomials , as well as thegenerating functions of Srivastava-Agarwal type. Furthermore, we establish links between the homogeneous -difference equations and transformation formulas.

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

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