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bsj-3834
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator has superior performance compared with other estimators.

 

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Publication Date
Sun Mar 30 2008
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Pyrolysis of High-density Polyethylene for the Production of Fuel-like Liquid Hydrocarbon
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Pyrolysis of high density polyethylene (HDPE) was carried out in a 750 cm3 stainless steel autoclave reactor, with temperature ranging from 470 to 495° C and reaction times up to 90 minute. The influence of the operating conditions on the component yields was studied. It was found that the optimum cracking condition for HDPE that maximized the oil yield to 70 wt. % was 480°C and 20 minutes. The results show that for higher cracking temperature, and longer reaction times there was higher production of gas and coke. Furthermore, higher temperature increases the aromatics and produce lighter oil with lower viscosity.

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Publication Date
Sun Dec 01 2019
Journal Name
Computers And Electronics In Agriculture
Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Development of an Integrated Construction Management System for Building Estimation
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Project management are still depending on manual exchange of information based on paper documents. Where design drawings drafting by computer-aided design (CAD), but the data needed by project management software can not be extracted directly from CAD, and must be manually entered by the user. The process of calculation and collection of information from drawings and enter in the project management software needs effort and time with the possibility of errors in the transfer and enter of information. This research presents an integrated computer system for building projects where the extraction and import quantities, through the interpretation of AutoCAD drawing with MS Access database of unit costs and productivities for the pricing and

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Publication Date
Tue Feb 28 2017
Journal Name
Journal Of Engineering
Estimation of Lifting Capacity for Selected Wells in Rumaila Field
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          This paper deals with studying the effect of hole inclination angle on computing slip velocity and consequently its effect on lifting capacity. The study concentrates on selected vertical wells in Rumaila field, Southern Iraq. Different methods were used to calculate lifting capacity. Lifting capacity is the most important factor for successful drilling and which reflex on preventing hole problems and reduces drilling costs. Many factors affect computing lifting capacity, so hence the effect of hole inclination angle on lifting capacity will be shown in this study. A statistical approach was used to study the lifting capacity values which deal with the effect of hole

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Estimation of electron temperature for SiO2 plasma induced by laser
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In this work; Silicon dioxide (SiO2) were fabricated by pulsed
laser ablation (PLA). The electron temperature was calculated by
reading the data of I-V curve of Langmuir probe which was
employed as a diagnostic technique for measuring plasma properties.
Pulsed Nd:YA Glaser was used for measuring the electron
temperature of SiO2 plasma plume under vacuum environment with
varying both pressure and axial distance from the target surface. The
electron temperature has been measured experimentally and the
effects of each of pressure and Langmuir probe distance from the
target were studied. An inverse relationship between electron
temperature and both pressure and axial distance was observed.

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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
Best estimation for the Reliability of 2-parameter Weibull Distribution
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This Research Tries To Investigate The Problem Of Estimating The Reliability Of Two Parameter Weibull Distribution,By Using Maximum Likelihood Method, And White Method. The Comparison Is done Through Simulation Process Depending On Three Choices Of Models (?=0.8 , ß=0.9) , (?=1.2 , ß=1.5) and (?=2.5 , ß=2). And Sample Size n=10 , 70, 150 We Use the Statistical Criterion Based On the Mean Square Error (MSE) For Comparison Amongst The Methods.

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimation and Forecasting of Evaporation Losses for Lake Mosul Dam
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Evaporation from water bodies is important and considered a major problem in dry and semi-dry regions, in this research the evaporation has been analyzed from two approaches: engineeringly and statistically. The engineering approach deals with the calculation of evaporation rates of Mosul Dam Lake. Three methods were used: pan evaporation class A, the combined and the mass-transfer. It was found that the values ​​obtained by pan evaporation class A method was the highest among the other, while the mass transfer method achieved the lowest results. The evaporation rates during the year ranged according to the first method (0.9–5.5) mm/day, second (0.7–11.5) mm/day and the last method (1.0039×106) m3/year, whi

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Publication Date
Mon Jul 25 2022
Journal Name
2022 Ieee 20th International Conference On Industrial Informatics (indin)
Robust Continuous Sliding Mode Controller for Uncertain Canonical Brunovsky Systems Using Reduced Order Extended State Observer
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A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its esti

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
comparison Bennett's inequality and regression in determining the optimum sample size for estimating the Net Reclassification Index (NRI) using simulation
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 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

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