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ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Thermodynamic function of valineacid in n-n dimethyl formamide mixtures from conductance measurement
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Some physical properties enthalpy (?H), entropy (?s), free energy (?G),capacities(?cp?) and Pka values) for valine in dimethyl foramideover the temperature range 293.15-318.15K, were determined by direct conductance measurements. The acid dissociation at six temperature was examined at solvent composition x2) involving 0.141 of dimethyl foramide . As results, calculated values have been used to determine the dissociation constant and the associated thermodynamic function for the valine in the solvent mixture over temperatures in the range 293.15-318.15 k. The Pka1, and Pka2 were increased with increasing temperature.

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Publication Date
Wed Feb 01 2012
Journal Name
Ibn Al-haytham Journal For Pure And Applied Science
Using Restricted Least Squares Method to Estimate and Analyze the Cobb-Douglas Production Function with Applicatio
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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between the Methods Estimate Nonparametric and Semiparametric Transfer Function Model in Time Series Using Simulation
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Publication Date
Sun Jun 30 2019
Journal Name
International Journal Of Research In Social Sciences And Humanities
CHARACTERISTICS OF THE POWER CHAIN FUNCTION CURVE AND ITS RELATION TO THE ACCURACY OF THE HIGH-JUMP JUMP IN THE HANDBALL
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The skill high-jump scoring is based on mechanical and physical abilities. The most important of all is the strength used by the player from the moment of preparation to the moment of scoring, which led the researchers to study the characteristics of the series of power chain functions of this skill according to (Biosyn System) The players of the national team's back line have a handball to find out the relationship between the properties of the power chain curve and the accuracy of the high jump to the upper and lower target angles. The aim of the research was to identify the values of the Force Series variables for the skill of the high-jump curve of the handball as well as the relationship between the properties of the power chain functi

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Publication Date
Tue May 11 2021
Journal Name
Research J. Pharm. And Tech
Association of Serum Renal Function Levels with Heart Failure Disease in Iraqi Patients
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Renal function tests are commonly used in clinical practice to look for renal disease, the most common includes the serum urea, uric acid and creatinine. Heart failure patients have a higher incidence of renal function test abnormalities than individuals who do not have heart failure disease. Fifty subjects of adults (male) were divided in to two groups, 25 subjects (healthy) as control (group1) and 25 subjects with heart failure (group 2). Our results indicate that serum uric acid, urea, and creatinine values were significantly elevated (P≤0.05) in patients group (2) compared with healthy group (1). The results also showed, the effect of age categories on uric acid blood urea nitrogen and creatinine values (P≤0.05) and there were no si

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Multiphase Flow
Application of artificial neural network to predict slug liquid holdup
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Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Mon Oct 01 2018
Journal Name
Conference: First International Conference On Water Resources
Modeling BOD of the Effluent from Abu-Ghraib Diary Factory using Artificial Neural Network October 2018
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The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Predicting biochemical oxygen demand at Al-Rustumiya wastewater treatment plant inlet using the artificial neural network
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