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Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international information network has showed that the error rate in the training and the testing process was about (10%) and that the results of the network query has given the results of acceptable accuracy statistically so that it was better than results obtained from multiple linear regression equation for the same data.

 

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
(Estimation and Analysis of the Cobb-Duglas Production Function for the Rail Transport Sector in Iraq for the Period 1990-2016 using the ARDL Model)
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Abstract:

Since the railway transport sector is very important in many countries of the world, we have tried through this research to study the production function of this sector and to indicate the level of productivity under which it operates.

It was found through the estimation and analysis of the production function Kub - Duglas that the railway transport sector in Iraq suffers from a decline in the level of productivity, which was reflected in the deterioration of the level of services provided for the transport of passengers and goods. This led to the loss of the sector of importance in supporting the national economy and the reluctance of most passengers an

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating the strategic performance of agricultural projects by adopting international indicators
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The aim of this research is to test the relationship of influence and correlation between strategic performance and its five dimensions (financial dimension, after internal processes, after internal customer satisfaction, after learning and growth, environmental and social dimension), by adopting international indicators in agricultural projects To determine the extent of the differences between the research variable and its dimensions, and then try to come out with a number of recommendations that contribute to the evaluation of agricultural projects and their performance by diagnosing and treating deviations, and based on the importance of the research topic in agricultural institutions. Institutions of the Environment and Soci

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Estimation of Cutoff Values by Using Regression Lines Method in Mishrif Reservoir/ Missan oil Fields
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Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.

This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.

The Mishrif formation was

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
Improving the productivity of single effect double slope solar still by modification simple
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The present paper is an experimental study to improve the productivity of the conventional solar still. This done by modifying conventional still in a way that the distilled basin is larger than distillation basin, thus providing an increase in the condensation surface and speeding up the condensation process. Moreover, increase in the dimensions of the distilled base helps coupling reflective panels to the distilled base to reflect incident solar radiation to the distillation basin. For this purpose , two solar stills were made, one conventional designand another made according to the proposed design. The two solar stills were tested during the period from February to July 2009 under varying weather conditions of Basra, Iraq (latitude o

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network
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Abstract<p>Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem</p> ... Show More
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Publication Date
Fri Nov 29 2019
Journal Name
Iraqi Journal Of Physics
CDD Study of Charge Density Distributions and Elastic Electron Scattering Cross Sections for some Stable Nuclei: Charge Density Distributions
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Publication Date
Wed Jan 05 2022
Journal Name
Journal Of Positive School Psychology
Influence Of Variance In Rest Interval For The Explosive Power Training For The Arms And Legs In The Light Of Some Biochemical Indicators For The Cellular Equilibrium Of The Volleyballers
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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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