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Use projection pursuit regression and neural network to overcome curse of dimensionality
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Abstract

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 the multiple regression as a sum of the nonlinear functions of the linear structures of the variables.

 Two approaches were used to solve the problem curse of dimensionality : the first approach is proposed projection pursuit regression method (PPR)  and The second approach is the method of neural networks (NN) representing by (Back Propagation of error)  which is one of the methods used in reducing dimensions . A simulated study was conducted to compare the methods used. The simulations were based on findings that showed that the method (NN) in this study gave better results than the (PPR) based on RMSE.

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
The effect of the activation functions on the classification accuracy of satellite image by artificial neural network
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Tue Jul 01 2025
Journal Name
Iraqi Journal Of Architecture And Planning
Assessing the Influence of Urban Street Network on Land Use Distribution in Historic Urban Cores
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposed method to estimate missing values in Non - Parametric multiple regression model
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In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

 

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Tree regression (TR), and Negative binomial regression (NBR) by Using Simulation.
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            In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare to the conditional logistic regression models with fixed and mixed effects for longitudinal data
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Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice & Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Sat Jun 08 2024
Journal Name
Obstetrics And Gynaecology Forum
Biochemical and Immunological responses to use dexamethasone in rats
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This study was conducted to determine the side effects of dexamethasone n some physiological and immunological criteria, which included, Measuring sugar level, liver (ALT, AST , LDH, Total protein) and kidney function (urea, createnine), total and differential count of W.B.C,CRP, TNF-α ,IL6,IL10. thirty rats were divided into two groups (15\ rat). G1: This group was considered negative control injection with normal saline, G2: This group was injected with 2 mg\kg dexamethasone. The results showed a significant increase in the level of enzymesALT, AST and sugar levels and decreased level of total protein in the group treated with the drug, also showed, a significant decrease in the total number of W.B.C an

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
The use of metal in ancient Syria in the manufacture of jewelry (ornamental tools in the third and second millennium BC and the molds used in their manufacture)
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 This research sheds light on the use of metal in the manufacture of jewelry, which is represented by ornamental tools in the period between the third and second millennium BC, in addition to the most important molds used in their manufacture. Man has been interested in metals since early ages, and was able to make tools that he uses in his daily life, especially jewelry. And the Syrian people got acquainted with the types of minerals, their characteristics, and how to deal with them. Minerals played an effective and prominent role in the economy of ancient Syria. Trade with those countries and secure their roads.

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