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Optimum Efficiency of PV Panel Using Genetic Algorithms to Touch Proximate Zero Energy House (NZEH)
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm under the standard test conditions (STC) and a comparison between the theoretical and experimental results is done to achieve maximum performance ranging from 0.15 to 0.16, particularly with an error of about - 0.333 for an experimental power of 30 Watts compared with the theoretical power of 30.1 Watts.  The results obtained by the genetic algorithm give the best value for efficiency at the range of 16% to 17% of solar radiation, from 500–600 W/m2. These values are almost identical to the efficiency obtained from the results of the operation, where the best value for efficiency in the experimental results was seen to be 15.7%.

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Publication Date
Wed Apr 15 2020
Journal Name
Journal Of Engineering Science And Technology
INFLUENCE OF A RIVER WATER QUALITY ON THE EFFICIENCY OF WATER TREATMENT USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Improvement of the Water Use Efficiency and Yield of Eggplant by Using Subsurface Water Retention Technology
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Sustainable crop production in a coarse soil texture is challenging due to high water permeability and low soil water holding capacity. In this paper, subsurface water retention technology (SWRT) through impermeable polyethylene membranes was placed at depth 35 cm below ground surface and within the root zone to evaluate and compare the impact of these membranes and control treatment (without using the membranes) on yield and water use efficiency of eggplant inside the greenhouse. The study was conducted in Al-Fahamah Township, Baghdad, Iraq during spring growing season 2017. Results demonstrated the yield and water use efficiencies were 3.483 kg/m2 and 5.653 kg/m3, respectively for SWRT treatment p

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Publication Date
Thu Jan 23 2020
Journal Name
Acoustics Australia
Absorption Coefficient of a Double-Layer Inhomogeneous Micro-perforated Panel Backed with Multiple Cavity Depths
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Double-layer micro-perforated panels (MPPs) have been studied extensively as sound absorption systems to increase the absorption performance of single-layer MPPs. However, existing proposed models indicate that there is still room for improvement regarding the frequency bands of absorption for the double-layer MPP. This study presents a double-layer MPP formed with two single MPPs with inhomogeneous perforation backed by multiple cavities of varying depths. The theoretical formulation is developed using the electrical equivalent circuit method to calculate the absorption coefficient under a normal incident sound. The simulation results show that the proposed model can produce absorption coefficient with wider absorption bandwidth compared w

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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Experimental Evaluation of the Performance of One-Axis Daily Tracking and Fixed PV Module in Baghdad, Iraq
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An attempt was made to evaluate the PV performance of one-axis daily tracking and fixed system for Baghdad, Iraq. Two experimental simulations were conducted on a PV module for that purpose. Measurements included incident solar radiation, load voltage and load current. The first experiment was carried out for six months of winter half of year to simulate the one-axis daily tracking. The azimuth angle was due south while the tilt angle was being set to optimum according to each day of simulation. The second experiment was done at one day to simulate the PV module of fixed angles. It is found that there is a significant power gain of 29.6% for the tracking system in respect to the fixed one. The one-axis daily tracking was much more effect

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Evaluation of routing protocol with multi-mobile sinks in WSNs using QoS and energy consumption parameters
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An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols i

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
A new smart approach of an efficient energy consumption management by using a machine-learning technique
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Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Efficiency Measurement Model for Postgraduate Programs and Undergraduate Programs by Using Data Envelopment Analysis
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Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.

 

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Evaluation the turbidity removal efficiency in Al-Wahda water treatment plant using statistical indicators
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Abstract<p>Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The predict</p> ... Show More
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Publication Date
Fri Dec 20 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
MEASURING RETURNSS TO SCALE, DISTRIBUTION EFFICIENCY AND ESTIMATING WHEAT PRODUCTION FUNCTION IN DHI QAR PROVINCE
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The aim of this research was to estimate the production function to measure returns to scale and distribution efficiency of  resources used in the production of wheat. Cross sectional data used of a random sample of 130 farmers in Dhi Qar Province. The results of the quantitative analysis of estimating production function showed that the double logarithmic form was the best estimated model based on economic and statistical indicators. However, that form suffered from heteroscedasticity and autocorrelation, so the robust regression technique was chosen. Value of returns to scale was 0.89 and this indicates decreasing returns to scale. This means that production function is in the second stage of the function. The results of the dist

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