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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
Fri Apr 21 2017
Journal Name
International Journal Of Science And Research
Effect of Coriandrumsativum Leaves Aqueous Extract on Structure and Function of Kidney in Male Albino Mice
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Abstract: Coriandrum sativum leaves are used in folk medicine to treat several diseases such as digestive system disorder, diabetes, and hyperlipidemia. This study was designed to investigate the effect of aqueous extract of Coriandrum sativum on the structure and function of kidney, 30 males of white Swiss mice Mus musculus were divided randomly to three groups with 10 mice in each group. Animals of first group (control group) had been given orally 0.1 ml of tap water, animals in the second group had been treated orally with 0.1 of single dose (125 mg/Kg b. w./day) of C. sativum leaves extract and animals in the third group has been treated orally with 0.1 ml (250mg/Kg. b. w./day) of the same extract for 30 days. At the end of experiment,

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Parametric Nonlinear Programming Approach with Fuzzy Queues Using Hexagonal Membership Functions
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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
A CERTAIN SUBCLASS OF MULTIVALENT HARMONIC FUNCTIONS DEFINED BY RUSCHEWEYH DERIVATIVES
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Abstract<p>We introduce a new class of harmonici multivalent functions define by generalized Rucheweyh derivative operator. We also obtain several interesting propertiesi such as sharp coefficienit estimates, distortioni bound, extreme points, Hadamardi product and other several results. Derivative; extreme points.</p>
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
An Extended Subclass of Meromorphic Multivalent Functions Involving Ruscheweyh Derivative Operator
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     In this paper, we introduce and discuss an extended subclass〖 Ą〗_p^*(λ,α,γ) of meromorphic multivalent functions involving Ruscheweyh derivative operator. Coefficients inequality, distortion theorems, closure theorem for this subclass are obtained.

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Publication Date
Fri Jan 13 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Kidney functions and electrolyte disturbance among Iraqi patients with bladder cancer
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المقدمة :يعد سرطان المثانة من بين أكثر أنواع السرطانات انتشارًا في جميع أنحاء العالم، حيث تم الإبلاغ عن 549,393 حالة جديدة في عام 2018 وما يقرب من ٪3 من جميع تشخيصات السرطان الجديدة و ٪2.1 من جميع وفيات السرطان ناتجة عن سرطان المثانة البولية. الاهداف: تهدف هذه الدراسة إلى استكشاف كفاءة وظائف الجهاز البولي بواسطة اجراء اختبارات وظائف الكلى ومستويات الايونات لمرضى سرطان المثانة. المنهجية: تم تحديد جميع الافراد الم

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Publication Date
Mon Jan 01 2018
Journal Name
Herald Namsca
STRUCTURE AND FUNCTIONS OF QUANTIFIER WORDS (IN ENGLISH, RUSSIAN AND JAPANESE)
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Abstract.. Quantitative characteristics of the surrounding world’s entities are expressed by the specific words – logical quantifiers. In a language, quantifiers are represented by the so-called quantifier words. Representing different degrees of the concentration of quantity, quantifier words in natural languages are positioned in a strict sequence – the quantifying scale. In terms of logic, it starts with nothingness (quantifier of meaningful nothingness), terminating at universality while in terms of language quantifier words, it is represented by the complex scale of quantifying words’ intensity. Logically speaking, this scale should start with the quantifier word ‘nothing’ to move all the way through increasing intensity ov

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

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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
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the speed of response of the exported quantity of crude oil to the increase in its prices using the model Impulse Response Functions (IRF) (Iraq case study) for the period (1978-2017)
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Abstract

     Oil is considered a commodity and is still an important and prominent role in drawing and shaping the Iraqi economic scene. The revenues generated from the export of oil are considered the main source of the general budget in cash flows.  

     Since the revenues consist of quantity and price and the latter is an external factor which is difficult to predict, The effect of any commodity on its price, which is proven in the theory of micro-economic, but it is observed through the research that the response is slow, which means not to take advantage of the rise in prices, by increasing the quantity exported, the result of several facto

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Using Neural Network with Speaker Applications
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In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

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