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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
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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Publication Date
Wed Sep 30 2020
Journal Name
Cfd Letters
Numerical Analysis for Solar Panel Subjected with an External Force to Overcome Adhesive Force in Desert Areas
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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Use some of the quality tools to improve the health service: Comparative research between Baghdad's and Yarmouk hospital educational
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Abstract

This research aims to improve the provided health service level inside Baghdad hospitals and the Yarmouk educational, as well as to shed light on the reality of the health service and the quality within the major operations room in both hospitals, as the operations room represent the research community, as was the use of some quality tools Pareto and Ishikawa diagram to measure and assess the level of quality provided, and include research problem to find out what are the problems and obstacles facing the process of improving quality in both hospitals, and whether there are scientifically accurate method to assess the quality of health service in Baghdad's Yarmouk hospital and educational . Where the researcher h

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
The use of value chain analysis of information in determining the most important the accounting information
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The use  analysis  value chain such  information in the provision as financial  so information quality meet and satisfy the needs of users such information , particularly investors and lenders   as the identification needs   financial information and the knowledge as their behavior influenced by that information can be based on the accounting profession to focus on improving their function in order to achieve its goal that satisfying their needs and rationalize their decisions . In accounting thought discovered fertile ground for users preferences as one of the entrances   theorising positive which is based on the need to include knowledge on accounting hypothesis that explain the

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Publication Date
Sun Jun 01 2014
Journal Name
Ibn Al-haitham Jour. For Pure & Appl. Sci.
Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis
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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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