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joe-2034
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data set sub-division into training, testing and holdout data sub-sets, and different number of hidden nodes in the hidden layer. It is found that it is not necessary that the nearest station to the station under prediction has the highest effect; this may be attributed to the high differences in elevation between the stations. It can also found that the variance is not necessary has effect on the correlation coefficient obtained.

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Ecology
Horizontal variability of some soil properties in wasit governorate by using time series analysis
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Scopus
Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Automatic Health Speech Prediction System Using Support Vector Machine
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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method
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Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Evaluation of Sustainable Spatial Suitability of Urban and Population Expansion in Al Hillah City Using Remote Sensing Techniques
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Abstract<p>The study focused on explaining urban expansion and sustainable development of urban land and explaining the role of population expansion in Al Hillah city, Al Hillah city in the center of Babylion Governorate located. The study relied on analyzing the population data of the city of Al Hillah for a period of time (22 years) for the period (2000-2022). This data was analyzed and its role in planning and designing residential areas and neighborhoods in the Al Hillah city was analyzed based on the standards of urban planning and sustainable growth of cities. Landsat 5TM was used in the investigation, Landsat 8OLI satellite data to retrieve the NDVI, NDBI, and NDWI. The findings showed th</p> ... Show More
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Publication Date
Sun Jan 01 2017
Journal Name
Spe/iatmi Asia Pacific Oil & Gas Conference And Exhibition
Influence of miscible CO2 flooding on wettability and asphaltene precipitation in Indiana Lime Stone
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Carbon dioxide (CO2) flooding is an EOR technique in which carbon dioxide is injected into the reservoir to improve the oil recovery. The reservoir oil and rock properties are altered when carbon dioxide interacts with the oil and rock present in the reservoir. Carbon dioxide injection alters the oil and rock properties by causing reduction in oil viscosity, oil swelling and wettability alteration of the rock. This paper will present a proposal to study the wettability alteration in carbonate formations during miscible carbon dioxide flooding. In miscible carbon dioxide flooding, the injection pressure of carbon dioxide would be kept above the minimum miscibility pressure. Thus carbon dioxide is miscible with the oil present in the reservoi

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Publication Date
Tue Nov 06 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Factors Contributing to Abdominal Post-Operative Wound Infections in Sulaimani Teaching Hospital
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Objectives: The study aims to assess some of the contributing factors to abdominal postoperative wound infection and
to find out the relationship between postoperative wound infections and some socio-demographic characteristics such as
age, gender, level of education, occupation and residential area.
Methodology: A descriptive study was carried out in Sulaimani Teaching Hospital (Kurdistan Region). The study has
started from January 15th up to October 31th, 2009. To achieve the study objectives, a purposive "non probability"
sample of (100) patients who have abdominal postoperative wound infection, Adult female and male patients who were
admitted to Sulaimani Teaching Hospital was selected.
The data were collected th

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Evaluated the level density for proton induced nuclear resonances in (P+48Ti) reaction using different models
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The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

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Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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