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An Efficient Algorithm for Fuzzy Linear Fractional Programming Problems via Ranking Function
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In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler and easier calculations as well as shortening in the procedures. The fuzzy fractional programming problem is the first reduced to a fractional programming problem and then solved with the technique to obtain the optimal solution. It has a power to give a best solution for supporting the solution theory proposed in this work, some numerical fuzzy fractional programming problem are included to ensure the advantage, efficiency and accuracy of the suggested algorithm. In addition, this research paper describes a comparison between our optimal solutions with other existing solutions for inequalities constrains fuzzy fractional program.

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Publication Date
Wed Nov 17 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Pearson coefficient matrix for studying the correlation of community detection scores in multi-objective evolutionary algorithm
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Publication Date
Sat Dec 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Low Cost Hardware Back Propagation Algorithm
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The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Low Cost Hardware Back Propagation Algorithm
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The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Fri Dec 15 2023
Journal Name
Iraqi Journal Of Laser
Evaluation of Lithium Disilicate Surface Morphology Treated with Er,Cr:YSGG and Fractional CO2 Laser
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Abstract: The use of indirect, all-ceramic restorations has grown in popularity among dentists. Studies have demonstrated that for indirect ceramic restorations to be effective over time, cement and ceramic must be bonded in a stable manner. Chemical, mechanical, and laser irradiation are among the methods used to precondition ceramic surfaces in order to increase bond strength.The objective of the study: This study was performed to investigate the roughness values and surface topography of lithium disilicate glass-ceramic treated with conventional methods and different Er,Cr:YSGG, and fractional CO2 laser conditioning parameters.Material and methods:<

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the continuity of the demand for money and its impact on the Iraqi dinar exchange rate for the period 1991-2013 function
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 Research Summary

It highlights the importance of assessing the demand for money function in Iraq through the understanding of the relationship between him and affecting the variables by searching the stability of this function and the extent of their influence in the Iraqi dinar exchange rate in order to know the amount of their contribution to the monetary policies of the Iraqi economy fee, as well as through study behavior of the demand for money function in Iraq and analyze the determinants of the demand for money for the period 1991-2013 and the impact of these determinants in the demand for money in Iraq.

And that the problem that we face is how to estimate the total demand for money in

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Thu May 05 2022
Journal Name
Karbala International Journal Of Modern Science
An economical source for peroxidase: maize cobs
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According to the current situation of peroxidase (POD), the relevant studies on this enzyme indicated its importance as a tool in clinical biochemistry and different industrial fields. Most of these studies used the fruits and vegetables as source of this enzyme. So that in order to couple the growing requirements for POD with the recent demands for reduc-ing disposal volume by recycling the plant waste, the aim of the present study was to extract POD through management of municipal bio-waste of Iraqi maize species. A simple, green and economical method was used to extract this enzyme. Our results revealed that maize cobs are rich sources of POD, where the activity of this enzyme was found to be 7035.54 U/g of cobs. In pilot experiments thi

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using simulation to compare between parametric and nonparametric transfer function model
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In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

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Publication Date
Sun Jul 31 2022
Journal Name
Journal Of Computational Innovation And Analytics (jcia)
PERFORMANCE MEASURE OF MULTIPLE-CHANNEL QUEUEING SYSTEMS WITH IMPRECISE DATA USING GRADED MEAN INTEGRATION FOR TRAPEZOIDAL AND HEXAGONAL FUZZY NUMBERS
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In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

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