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Estimate and Analysis the Availability of Generator in Electric Power Plant Using ANN
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The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching of Feed-Forward, Back-Propagation. Operating data from the years 2015–2017 were used to calculate the availability by traditional method (Weibull distribution) and train the ANNs, while data from the year 2018 of operation were used to verify the model. The study implies that the ANN may be able to forecast the availability of the generator with a correlation coefficient (R) 0.99874 and a Mean Square Error (MSE) 5.6937E-06 between the availability predicted by ANN and Weibull distribution output.

 

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
The Effect of Magnetic Water for Chemical Fertilizer in Tomato Plant
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The research aims to find ways to minimize the use of quantities of chemical fertilizers in agriculture in order to get to an environment that is free of contaminants. Magnetized water technology used in the experience of planting seeds of tomatoes Thomson type to obtain a higher efficiency to absorb fertilizer NRK in the protected environment of the period from February to June. Magnetized water system used locally made levels Gaues (4800,2500,1500) concentrations of 50 to 100% for each level and the rate of (4) replicates, and results indicated that the severity of the magnet (4800 Gaues) and a concentration of 50% gave the highest percentage of tomato fruit size and intensity ( 1500 Gaues) and a concentration of 100% did not give any inc

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Use Dynamic Bayesian network to estimate the reliability of Adamia Water Network
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Abstract\

In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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Publication Date
Fri Sep 01 2017
Journal Name
2017 9th Computer Science And Electronic Engineering (ceec)
Modelling the power cost and trade-off of live migration the virtual machines in cloud-radio access networks
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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Predicting biochemical oxygen demand at Al-Rustumiya wastewater treatment plant inlet using the artificial neural network
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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Effect of plant growth regulators on callus induction and Rutin production of Ricinus communis L. plant
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Ricinus communis L. is an important medical plant hence it contains many active compounds. The aim of this research is to study the effect of plant growth regulators on callus induction and Rutin concentration. A combination of Benzyle adenine (BA) and Indol Acetic acid (IAA) at (0.0,1.0,2.0) mg/L was added to the media, the highest fresh weight of the induced callus from stem explant was (4.97) gr . at (1.0,1.0) mg/L BA and IAA consenquently the same combination gave the highest dry weight of callus (0.42) gr. while the combination at (2.0,1.0) mg/L BA and IAA gave the highest fresh weight of induced callus from Leaves explant (5.28) gr., then (2.0,1.0) mg/L BA and IAA gave the highest dry weight for callus induced from leaves at (0.55

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the relationship between the prices of wheat and rice importer in Iraq and crude oil prices and the exchange rate using the ARDL model
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Since the beginning of 21st century, the prices of Agricultural crops have increased. This Increases is accompanied with that increases of crude oil prices and fluctuation of a dollar exchange rate as a dominant currency used in the global trade. The paper aimed to analysis the short run and long run cointegration relationships between prices of some of Agricultural crops imported by Iraq such as wheat and rice crops and both the crude oil prices and the Iraq dinar exchange rate a gained America dollar using ARDL model. The results show the long run equilibrium between they three variable throng the error correction mechanizem. The results also show the significant and economically sound effects of cru

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Publication Date
Wed Aug 27 2025
Journal Name
2025 International Conference On Electrical, Communication And Computer Engineering (icecce)
A Hybrid Deep Learning Approach for Fault Classification in Electric Vehicle Drive Motors
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A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

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Publication Date
Sun Jul 01 2018
Journal Name
Materials Letters
Temperature stable electric field-induced strain in Er-doped BNT-BT-BKT ceramics
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Publication Date
Mon Nov 05 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EFFECT OF PLANT DENSITIES ON THE GROWTH AND YIELD OF SUNFLOWER Helianthus annuus L.: EFFECT OF PLANT DENSITIES ON THE GROWTH AND YIELD OF SUNFLOWER Helianthus annuus L.
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A field experiment was conducted at the experimental field of botanical garden, faculty of science, university of Baghdad, in order to study the effect of plant density on growth and yield of two local cultivars of sunflower (Sin Althieb and Shumose). The densities used were 4.4 and 8.8 plant/m2. The results showed difference between cultivars in their agronomic traits and their yields. There was a significant increase in plant height and leaf area index by increasing the plant density, while head diameter, number of seeds and leaf area decreased. But the most significant effect was the increasing in yield and biological yield by increasing the plant density. There was an increase by 72% and 58% in the yield and 79% an

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