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Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postponement of delay of interim payments is at the forefront of delay factors caused by the employer’s decision. Even the least one is to leave the job site caused by the contractor’s second part of the contract, the repeated unjustified stopping of the work at the site, without permission or notice from the client’s representatives. The developed model was applied to about 97 projects and used as a prediction model. The decision tree model shows higher accuracy in the prediction.</p>
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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Engineering
Intelligence in Construction between Contemporary and Traditional Architecture
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The authentic traditional architecture proved that it is very convenient to the environmental and social regulations where it appeared and lasted for hundred of years.

This traditional architecture got the intelligence in providing thermal comfort for their occupants by the intelligent usage of the building materials and the intelligent planning and designs which took in consideration the climatic condition and the aerodynamics of the whole city as one ecological system starting from the cold breeze passing through its narrow streets till it enters the dwelling units and glides out through the wind catchers.

This architecture had been neglected and replaced by modern imported architecture which had collap

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Performance evaluation of small and medium-sized enterprises according to the entrance of the scorecard applied study in company Al fadly for construction industries
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The research Aim is to provide support to small enterprises by providing tools that enable measurement and test their performance and identifying weaknesses and work on them is determined by the problem of searching using traditional assessment methods for small projects with only financial performance measurement standards that do not provide a complete picture of the performance of these projects so use the balanced scorecard the four pillars (financial, customer, learning and growth, and internal processes) and identify deviations and work on them through the use of the outputs of the programme (probe), PROmoting Business Excellence-PROBE), which It is a model of performance evaluation, with which you can deve

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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
*Email:[email protected] 2131 The Accuracy of Prediction for the Models IRI- 2012 and VOACAP in Measurements foF2 Over Iraq during High Solar Activity Level
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The accuracy of IRI- 2012 and VOACAP models during high solar activity level have been tested to know which of them is more accurate in predicting hourly foF2 values for three Iraqi cities (Baghdad, Mosul and Basrah). The results indicated that the accuracy of them increases for all hours during Spring and Summer and decreases during Winter and Autumn especially at hours near to sunrise; i.e., both of two models have the same accuracy. And that the foF2 values predicted by VOACAP model are higher than that predicted by IRI- 2012 model for all seasons.

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Use digital classification to follow change detection of al Razzazah sebkha For the period(1976-2013)
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The Sebkha is considered the evaporative geomorphological features, where climate plays an active role. It forms part of the surface features in Mesopotamia plain of Iraqi, which is the most fertile lands, and because of complimentary natural and human factors turned most of the arable land to the territory of Sebkha lands. The use satellite image (Raw Data), Landsat 30M Mss for the year 1976 Landsat 7 ETM, and the Landsat 8 for year 2013 (LDCM) for the summer Landsat Data Continuity Mission and perform geometric correction, enhancements, and Subset image And a visual analysis Space visuals based on the analysis of spectral fingerprints earth's This study has shown that the best in the discrimination of Sebkha Remote sensing techniques a

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Subsurface 3D Prediction Porosity Model from Converted Seismic and Well Data Using Model Based Inversion Technique
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Seismic inversion technique is applied to 3D seismic data to predict porosity property for carbonate Yamama Formation (Early Cretaceous) in an area located in southern Iraq. A workflow is designed to guide the manual procedure of inversion process. The inversion use a Model Based Inversion technique to convert 3D seismic data into 3D acoustic impedance depending on low frequency model and well data is the first step in the inversion with statistical control for each inversion stage. Then, training the 3D acoustic impedance volume, seismic data and porosity wells data with multi attribute transforms to find the best statistical attribute that is suitable to invert the point direct measurement of porosity from well to 3D porosity distribut

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Publication Date
Thu Jun 01 2017
Journal Name
Professional Safety
Six Sigma & Construction Safety
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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving Nonlinear Second Order Delay Eigenvalue Problems by Least Square Method
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     The aim of this paper is to study the nonlinear delay second order eigenvalue problems which consists of delay ordinary differential equations, in fact one of the expansion methods that is called the least square method which will be developed to solve this kind of problems.

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
A Proposal Algorithm to Solve Delay Constraint Least Cost Optimization Problem
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Traditionally, path selection within routing is formulated as a shortest path optimization problem. The objective function for optimization could be any one variety of parameters such as number of hops, delay, cost...etc. The problem of least cost delay constraint routing is studied in this paper since delay constraint is very common requirement of many multimedia applications and cost minimization captures the need to
distribute the network. So an iterative algorithm is proposed in this paper to solve this problem. It is appeared from the results of applying this algorithm that it gave the optimal path (optimal solution) from among multiple feasible paths (feasible solutions).

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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Extend Differential Transform Methods for Solving Differential Equations with Multiple Delay
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In this paper, we present an approximate analytical and numerical solutions for the differential equations with multiple delay using the extend differential transform method (DTM). This method is used to solve many linear and non linear problems.

 

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Concepts of statistical learning and classification in machine learning: An overview
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Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

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