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Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction
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This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, efficiency and reliability in predicting time series.

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Thu Sep 08 2016
Journal Name
Telecommunication Systems
Design and simulation analysis of network-based fully distributed mobility management in flattened network architecture
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Publication Date
Thu Jan 12 2017
Journal Name
Journal Of Agricultural And Food Chemistry
Using Standing Gold Nanorod Arrays as Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Detection of Carbaryl Residues in Fruit Juice and Milk
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Publication Date
Sat Oct 19 2024
Journal Name
Iraqi Statisticians Journal
Forecasting Gold prices by hybrid ANFIS-based algorithm
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In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Development of Pavement Maintenance Management System for Baghdad Urban Roadway Network
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The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o

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Publication Date
Mon Mar 30 2026
Journal Name
Iraqi Journal Of Science
Facial Expression Recognition Using Deep Learning EfficientNetB0
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Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
A comparison of cross sections for Selenium -73 radioisotopes produced by accelerators and reactors
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Background: Selenium-73 with half- life of 7.15 hour emits β+ in nature and has six stable isotopes which are ( 74Se,76Se,77Se,78Se,80Se and 82Se ). Selenium-73 has many applications in technology and radioselenium compounds of metallic have found various applications in medicine. Objective:  To make a comparison between different reactions that produced cross sections of Se-73 radioisotopes. Subjects and methods: The feasibility of the production of Selenium -73 via various nuclear reactions was investigated. Excitation functions of 73Se production by the reactions of 75As (p,3n), 169Tm( d,x), 74Se, natSe, natBr (p,x) , 75As (d,4n), natGe (3He,x), 70Ge (α, n), and 72Ge (α, 3n) and neutron capture were calculated using the avail

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
A comparison of cross sections for Selenium -73 radioisotopes produced by accelerators and reactors
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Background: Selenium-73 with half- life of 7.15 hour emits β+ in nature and has six stable isotopes which are ( 74Se,76Se,77Se,78Se,80Se and 82Se ). Selenium-73 has many applications in technology and radioselenium compounds of metallic have found various applications in medicine.

Objective:  To make a comparison between different reactions that produced cross sections of Se-73 radioisotopes.

Subjects and methods: The feasibility of the production of Selenium -73 via various nuclear reactions was investigated. Excitation functions of 73Se production by the re

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Nonparametric Binary Logistic Regression
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In this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some methods for estimating Poisson-Weibull distribution parameters
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In this paper was discussed the process of compounding two distributions using new compounding procedure which is connect a number of life time distributions ( continuous distribution ) where is the number of these distributions represent random variable distributed according to one of the discrete random distributions . Based on this procedure have been compounding zero – truncated poisson distribution with weibell distribution to produce new life time distribution having three parameter , Advantage of that failure rate function having many cases ( increasing , dicreasing , unimodal , bathtube) , and study the resulting distribution properties such as : expectation , variance , comulative function , reliability function and fa

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