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Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parameters. A databases from one well drilled in carbonate environments were subjected to the predictive methods. Each raw dataset is described by eight parameters including rate of penetration (ROP), true vertical depth (TVD), weight on bit (WOB), bit rotational speed (RPM), torque (TQ), flow rate (Q), equivalent circulating density (ECD), standpipe pressure (SPP), and unconfined compressive strength (UCS). First, both MRA and ANNs are tested as predictive methods. The prediction capacity of each model was also verified by using two-based error metrics: the determination coefficient (R2) and the mean square error (MSE).</p><p>The current results support the evidence that MRA and ANNs are able to be effectively utilize the drilling data, and thus provide accurate ROP prediction. However, more attention to the multiple regression analysis is required where it is implemented for ROP prediction. ANNs appear to be more conservative in predicting ROP than MRA as indicated by a higher value R2 (0.96) and lower value MSE (1.89) of the ANN model. Considering the input parameters, the obtained results showed that TVD, WOB, RPM, SPP, and ECD had the greatest effect on estimated ROP-conditions, followed in decreasing by pump flow rate, drilling torque, and rock strength. Another important point that highlights in this study is that the drilling rate may increase with depth in carbonate rocks because of their heterogeneity. This study presents new models to estimate ROP from other parameters which can help the driller to achieve an optimal drilling rate through monitoring controllable parameters.</p>
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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Mon Jul 01 2024
Journal Name
Ecological Engineering &amp; Environmental Technology
Use of Nano Co-Ni-Mn Composite and Aluminum for Removal of Artificial Anionic Dye Congo Red by Combined System
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The removal of congo red (CR) is a critical issue in contemporary textile industry wastewater treatment. The current study introduces a combined electrochemical process of electrocoagulation (EC) and electro-oxidation (EO) to address the elimination of this dye. Moreover, it discusses the formation of a triple composite of Co, Mn, and Ni oxides by depositing fixed salt ratios (1:1:1) of these oxides in an electrolysis cell at a constant current density of 25 mA/cm2. The deposition ended within 3 hours at room temperature. X-ray diffractometer (XRD), field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and energy dispersive X-ray (EDX) characterized the structural and surface morphology of the multi-oxide sedim

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Publication Date
Mon Nov 19 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Study of the impact of foreign direct investment in the Iraqi tax system using the factorial analysis: (principal components)
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The tax system, like any other system, as a set of elements and parts that complement each other and are interrelated and interact to achieve specific goals, and is a natural  reflection of the economic, social and political conditions prevailing in society, and therefore the objectives of tax policy formulated in line with the objectives of economic policy in general, which means that any change in economic policy clearly affects fiscal policy measures and fiscal policy in particular.

The problem of searching for the impact of foreign direct investment in the Iraqi tax system was focused on the study  the of foreign direct investment and therole played in developing and improving the economic reality and its implicatio

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Publication Date
Tue Oct 29 2019
Journal Name
Journal Of Engineering
Mobile-based Human Emotion Recognition based on Speech and Heart rate
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Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Use projection pursuit regression and neural network to overcome curse of dimensionality
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This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Compared Some Estimators Ordinary Ridge Regression And Bayesian Ridge Regression With Practical Application
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Maulticollinearity is a problem that always occurs when two or more predictor variables are correlated with each other. consist of the breach of one basic assumptions of the ordinary least squares method with biased estimates results, There are several methods which are proposed to handle this problem including the  method To address a problem  and  method To address a problem , In this research a comparisons are employed between the biased   method and unbiased   method with Bayesian   using Gamma distribution  method  addition to Ordinary Least Square metho

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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Robust Circular S and Circular Least Squares Estimators for Circular Regression Model using Simulation
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In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Importance of Banking Merger To Promote Iraqi Banks Faltering and Slow Using The Logistic Regression Model
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Abstract

The research examined with the importance banking merger to address the situation of Troubled banks in Iraq, Through The use of Logistic Regression Model. . The study attempted to present a conceptual aspect of banking merger and logistic regression, as well as the applied aspect which includes a sample consisting of six private Iraqi banks, and the hypothesis of the study is that the promotion of mergers among banks has positive impacts on improving the efficiency of performance of troubled banks, which contributes to the increase of banking services, raise of their financial indicators and the high liquidity and profits of the new banking entity as it is a way to overcome the prevailing banking crises.

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Innovation, Management And Technology
Intelligent Magneto-Rheological Fluid Directional Control Valve
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There are many configurations of directional control valve. Directional control valve has complex construction, such as moving spool to control the direction of actuator and desired speed. Magneto-rheological (MR) fluid is one of controllable fluids. Utilizing the MR fluid properties, direct interface can be realized between magnetic field and fluid power without the need for moving parts like spool in directional control valves. This paper presents the design of multi configuration MR directional control valve. The construction and the principle of work of the valve are presented. The experiment was conducted to show the working principle of the valve functionally. The valve worked proportionally to control the direction and speed of hydra

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Publication Date
Wed Aug 10 2022
Journal Name
Mathematics
Modeling and Analysis of the Influence of Fear on the Harvested Modified Leslie–Gower Model Involving Nonlinear Prey Refuge
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Understanding the effects of fear, quadratic fixed effort harvesting, and predator-dependent refuge are essential topics in ecology. Accordingly, a modified Leslie–Gower prey–predator model incorporating these biological factors is mathematically modeled using the Beddington–DeAngelis type of functional response to describe the predation processes. The model’s qualitative features are investigated, including local equilibria stability, permanence, and global stability. Bifurcation analysis is carried out on the temporal model to identify local bifurcations such as transcritical, saddle-node, and Hopf bifurcation. A comprehensive numerical inquiry is carried out using MATLAB to verify the obtained theoretical findings and und

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