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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
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
''The use of factor analysis to identify the leading factors to high blood pressure.''A field study in Baghdad hospitals
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Abstract :

    In view of the fact that high blood pressure is one of the serious human diseases that a person can get without having to feel them, which is caused by many reasons therefore it became necessary to do research in this subject and to express these many factors by specific causes through studying it using (factor analysis).

  So the researcher got to the five factors that explains only 71% of the total variation in this phenomenon is the subject of the research, where ((overweight)) and ((alcohol in abundance)) and ((smoking)) and ((lack of exercise)) are the reasons that influential the most in the incidence of this disease.

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Thu Sep 15 2022
Journal Name
Romanian Neurosurgery
Impact of dome projection on operative steps during clipping of a ruptured pure posteriorly directed posterior communicating artery aneurysms
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Background: Ruptured posterior communicating artery (PCoA) aneurysms are common; they usually present with subarachnoid haemorrhage (SAH) and oculomotor nerve palsy. The aneurysmal dome projection may influence the safety access and aneurysmal neck clipping. Here, we discuss additional intraoperative steps that may be required to widen the surgical field to ensure safe surgical clipping of a rupture pure posteriorly directed PCoA aneurysm. Case description: A previously healthy 38-year-old male reported sudden severe headache and disturbed level of consciousness with a Glasgow coma scale (GCS) of 13. His initial computed tomography (CT) scan of the head showed SAH in the basal cistern. 3D-constructed CT angiography (CTA) revealed a

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Publication Date
Sat Dec 21 2024
Journal Name
Edelweiss Applied Science And Technology
Using count regression models to investigate the most important economic factors affecting divorce in Iraq
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The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Some Robust Estimators for Estimate parameters logistic regression model to Binary Response – using simulation)).
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 The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.                                                          

Among the problems that appear as a result of the use of some statistical methods I

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Using the artificial TABU algorithm to estimate the semi-parametric regression function with measurement errors
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
استعمال الاستدارة و فرز الاستدارة في تفسیر نمط توزیع واشكال وحدات خرائط الترب في مشروع المسیب الكبیر
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Large – Almusseiyab soils survey project in mid Mesopotamian plain have
been chosen , because of its variation in soil series and reiteration map units, to
calculate the roundness of map units and roundness sorting values, in order to use
them as a pattern of map units shapes which help in interpret the distribution and
shapes of map units, which they were (18) soil series in (141) reiteration. Calculate
each map units roundness have been done and its value ranged between (0.09) to
(0.51), The average of roundness ranged between (0.250) for each MM1, MW5
soil series ,and (0.317) for DW45 . 99.30 % of samples were not good roundness
and with many sineuosity. The second group was a largest percentage 38.88 % with<

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Publication Date
Sun Jul 12 2020
Journal Name
International Journal Of Research In Social Sciences And Humanities
THE USE OF PRODUCT LIFE CYCLE ASSESSMENT TECHNOLOGY TO ACHIEVE PRODUCT SUSTAINABILITY
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This research aims to demonstrate the knowledge pillars of the product life cycle assessment technique and how to measure the cost according to this technique, and to clarify its role in reducing costs, improving product quality and optimizing the use of available resources, and a set of results has been reached, the most important of which are: The separation of environmental costs through the use of product life cycle assessment technique helps the Management in handling the increase of these costs, reducing the rates of environmental pollution and preserving resources, which contributes to achieving the sustainability of the product, and based on the results obtained, a set of recommendations were presented, the most important of which w

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using Mehar method to change fuzzy cost of fuzzy linear model with practical application
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  Many production companies suffers from big losses because of  high production cost and low profits for several reasons, including raw materials high prices and no taxes impose on imported goods also consumer protection law deactivation and national product and customs law, so most of consumers buy imported goods because it is characterized by modern specifications and low prices.

  The production company also suffers from uncertainty in the cost, volume of production, sales, and availability of raw materials and workers number because they vary according to the seasons of the year.

  I had adopted in this research fuzzy linear program model with fuzzy figures

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