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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
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression based on Non-Linear Polynomial Prediction Model
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Publication Date
Thu May 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Channel Estimation and Prediction Based Adaptive Wireless Communication Systems
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Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Vertical Stress Prediction for Zubair Oil Field/ Case Study
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Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

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Publication Date
Fri Nov 28 2025
Journal Name
Arabian Journal For Science And Engineering
Role of Artificial Intelligence in Enhancing Efficiency and Sustainability in Middle Eastern Oil and Gas: A Review
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This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
The Prediction of the Electromagnetic Properties and the ?(E2/M1) of 110-116Cd-Isotopes in IBM Model
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The Nuclear structure of 110-116Cd isotopes was studied theoretically in the framework of the interacting boson model of IBM-l and IBM-2. The properties of the lowest mixed symmetry states such as the 1+, 2+ and 3+ levels produced by the IBM-2 model in the vibrational-limit U(5) of Cd - isotopes are studied in details. This analysis shows that the character of mixed symmetry of 2+ is shared between and states in 110-114Cd – isotopes, the large shar goes to s, while in isotope, the state is declared as a mixed symmetry state without sharing. This identification is confirmed by the percentage of F-spin contribution. The electromagnetic properties of E2 and Ml operators were investigated and the results were analyzed. Various

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Engineering
A Prediction Formula for The Estimation of Sediment Load in The Upper Reach of Al-Gharraf River
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The presence of deposition in the river decreases the river flow capability's efficiency due to the absence of maintenance along the river. In This research, a new formula to evaluate the sediment capacity in the upstream part of Al-Gharraf River will be developed. The current study reach lies in Wasit province with a distance equal to 58 km. The selected reach of the river was divided into thirteen stations. At each station, the suspended load and the bedload were collected from the river during a sampling period extended from February 2019 till July 2019. The samples were examined in the laboratory with a different set of sample tests. The formula was developed using data of ten stations, and the other three s

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
The Use of the Artificial Damped Outrigger Systems in Tall R.C Buildings Under Seismic Loading
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This paper studies the combination of fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. This optimizes the accuracy of the dynamic response and by providing higher level of damping, basically minimizes the wanted stiffness of the structure while at the same time optimizing the achievement.

     The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximu

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Fatigue Characterization for Composite Materials used in Artificial Socket Prostheses with the Adding of Nanoparticles
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Abstract<p>The prostheses sockets use normally composite materials which means that their applications may be related with the human body. Therefore, it was very necessary to improve the mechanical properties of these materials. The prosthetic sockets are subjected to varying stresses in gait cycle scenario which may cause a fatigue damage. Therefore, it is necessary or this work to modify the fatigue behavior of the materials used for manufacturing the prostheses sockets. In this work, different Nano particle materials are used to modify the mechanical properties of the composite materials, and increase the fatigue strength. By using an experimental technique, the effect of using different volu</p> ... Show More
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Publication Date
Thu Oct 22 2020
Journal Name
2020 4th International Symposium On Multidisciplinary Studies And Innovative Technologies (ismsit)
Artificial Intelligence in Smart Agriculture: Modified Evolutionary Optimization Approach for Plant Disease Identification
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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Harnessing Technological Innovation and Artificial Intelligence in Iraqi Commercial Banks to Achieve Sustainability
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