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Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered from five drilled wells were involved in modeling process.Approximatlly,85 % of these data were used for training the ANN models, and 15% to assess their accuracy and direction of stability. The results of the simulation showed good matching between the raw data and the predicted values of ROP by Artificial Neural Network (ANN) model. In addition, a good fitness was obtained in the estimation of drilling cost from ANN method when compared to the raw data.

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Publication Date
Tue Aug 02 2011
Journal Name
J. College Of Education / Al-mustansiriya University
Synthesis and characterization of mixed ligand complexes of some metals with ( L- phenylalanine and nicotinamide)
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This paper presents the synthesis and study of some new mixed-ligand complexes containing nicotinamide(C6H7N2O) symbolized (NA) and phenylalanine (C9H11NO2)symbolized (pheH)] with some metal ions. The resulting products were found to be solid crystalline complexes which have been characterized by :Melting points, Solubility, Molar conductivity. determination the percentage of the metal in the complexes by flame(AAS), magnetic susceptipibility, Spectroscopic Method [FT-IR and UV-Vis]. The proposed structure of the complexes using program , chem office 3D(2006) . The general formula have been given for the prepared complexes : [M(NA)2(phe)]cl M(II): Mn(II) ,Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) & Hg(II)). NA = Nicotinamide= C6

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Publication Date
Sun Jan 01 2012
Journal Name
Al-mustansiriya J. College Of Education
Synthesis and characterization of mixed ligand complexes of some metals with ( L- phenylalanine and nicotinamide)
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This paper presents the synthesis and study of some new mixed-liagnd complexes containing nicotinamide(C6H7N2O) symbolized (NA) and phenylalanine (C9H11NO2)symbolized (pheH)] with some metal ions. The resulting products were found to be solid crystalline complexes which have been characterized by :Melting points, Solubility, Molar conductivity. determination the percentage of the metal in the complexes by flame(AAS), magnetic susceptipibility, Spectroscopic Method [FT-IR and UV-Vis]. The proposed structure of the complexes using program , chem office 3D(2006) . The general formula have been given for the prepared complexes :[M(NA)2(phe)]cl M(II): Mn(II) ,Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) & Hg(II) . NA = Nicotinamide= C6H7N2O Phe -

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Publication Date
Fri Aug 13 2021
Journal Name
Journal Européen Des Systèmes Automatisés
Proxy-based sliding mode vibration control with an adaptive approximation compensator for euler-bernoulli smart beams
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Proxy-based sliding mode control PSMC is an improved version of PID control that combines the features of PID and sliding mode control SMC with continuously dynamic behaviour. However, the stability of the control architecture maybe not well addressed. Consequently, this work is focused on modification of the original version of the proxy-based sliding mode control PSMC by adding an adaptive approximation compensator AAC term for vibration control of an Euler-Bernoulli beam. The role of the AAC term is to compensate for unmodelled dynamics and make the stability proof more easily. The stability of the proposed control algorithm is systematically proved using Lyapunov theory. Multi-modal equation of motion is derived using the Galerkin metho

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
CA 27-29: A Valuable Marker for Breast Cancer Management in Correlation with CA 15-3
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Biomathematics
A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain
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This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Publication Date
Wed Dec 03 2025
Journal Name
Journal Of Taibah University For Science
Effective computational methods for solving the hyperbolic one-dimensional wave equation with nonlocal mixed boundary conditions
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This paper considers approximate solution of the hyperbolic one-dimensional wave equation with nonlocal mixed boundary conditions by improved methods based on the assumption that the solution is a double power series based on orthogonal polynomials, such as Bernstein, Legendre, and Chebyshev. The solution is ultimately compared with the original method that is based on standard polynomials by calculating the absolute error to verify the validity and accuracy of the performance.

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Finding the Best Route for Connecting Citizens with Service Centers in Baghdad Based on NN Technology
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     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

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Publication Date
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Physics
The transition rates for 232Th using the two component particle-hole state density with different corrections
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The particle-hole state densities have been calculated for 232Th in
the case of incident neutron with  ,  1 Z Z T T T T and   2 Z T T .
The finite well depth, surface effect, isospin and Pauli correction are
considered in the calculation of the state densities and then the
transition rates. The isospin correction function ( ) iso f has been
examined for different exciton configurations and at different
excitation energies up to 100 MeV. The present results are indicated
that the included corrections have more affected on transition rates
behavior for        , , and    above 30MeV excitation energy

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