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jeasiq-1925
Compare Prediction by Autoregressive Integrated Moving Average Model from first order with Exponential Weighted Moving Average
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The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traffic accidents in the province of Dhi Qar Governorate for the period from (Jan. 2011) to (Aug. 2019). It was found through the research that the model studied is well of the traffic accident, we can predict dangerous traffic accident using this model and reduce the aggravation through Develop plans strategic of the roads.

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Publication Date
Wed Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
A Viscoplastic Modeling for Permanent Deformation Prediction of Rubberized and Conventional Mix Asphalt
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
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

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Publication Date
Sat Apr 01 2023
Journal Name
Fluid Phase Equilibria
Prediction of solubility of vitamins in the mixed solvents using equation of state
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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
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 postpo</p> ... Show More
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Publication Date
Thu Sep 06 2018
Journal Name
Al-khwarizmi Engineering Journal
Bone Defect Animal Model for Hybrid Polymer Matrix Nano Composite as Bone Substitute Biomaterials
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Addition of bioactive materials such as Titanium oxide (TiO2), and incorporation of bio inert ceramic such as alumina (Al2O3), into polyetheretherketone (PEEK) has been adopted as an effective approach to improve bone-implant interfaces. In this paper, hot pressing technique has been adopted as a production method. This technique gave a homogenous distribution of the additive materials in the proposed composite biomaterial. Different compositions and compounding temperatures have been applied to all samples. Mechanical properties and animal model have been studied in all different production conditions. The results of these new TiO2/Al2O3/PEEK biocomposites with different

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Publication Date
Wed May 24 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
PREPARATION CONCETRATE PROTEIN FROM AL- ZAHDI DATE’S PITS AND USED FOR BISCUIT FORTIFICATION: PREPARATION CONCETRATE PROTEIN FROM AL- ZAHDI DATE’S PITS AND USED FOR BISCUIT FORTIFICATION
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This study was conducted to prepare protein concentrates from AL-Zahdidate’s pits by using alkaline methods where the chemical composition of the pits were (7.30, 1.04, 5.80, 8.68 and 77.19) % for each of the moisture, ash, protein, fat and carbohydrates respectively and the chemical composition of the concentrate protein was (6.62, 4.10, 26.70, 0.93, and 58.65) % respectively. The content of protein concentrate from the metallic elements (144.07, 25.11, 15.02, 0.49, 0.59, 0.27, 0.22 and 234.6) mg/ 100 g each of potassium, magnesium, calcium, iron, manganese, copper, zinc and phosphorus respectively. The results of SDS-PAGE showed five bands with weights molecular ranged between 11000-70000 Dalton. Give the biscuit which contain protei

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Publication Date
Fri Mar 01 2024
Journal Name
Annales Pharmaceutiques Françaises
Adopting video assignments as a tool to improve first-year pharmacy students class engagement
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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Historical inductive study on   Ground forces of the army during the first Abbasid era
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This study sought to give a general picture of the organizations and formations of the ground forces of the Abbasid army in its first era, in preparation and armament and continuous development of the mechanisms to help maintain the moral and spiritual morale in the fighting.
Therefore, the caliphs' interest in building the army, organizing it, arming it, choosing competent leaders, and providing them with various weapons in terms of production and storage, as well as taking care of fortifying the cities and gaps in determination and determination, and embarked on construction and restoration, where amazing speed and acted according to the circumstances. During the first Abbasid era, there were significant developments in the military

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
First Record of Mint Leaf Beetle, Chrysolina herbacea (Duftschmid, 1825), (Coleoptera: Chrysomelidae) in Iraq
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The  insect is diagnosed and named by the National Center of Biotechnology Information (NCBI), USA as the Mint leaf Beetle Chrysolina herbacea alnadawi (Duftschmid, 1825), (Coleoptera: Chrysomelidae). The diagnosis was performed depending on the DNA analysis by 73% similarity with Chrysolina herbacea (Duftschmid, 1825) sequence, In the present study. It is recorded as a new insect pest on mint plant Mentha  puleguim (L,1753) (Lamiaceae). DNA analysis confirmend that it is recorded for the first time in Iraq and the Arab world as well as the Middle East. Those insects were observed initially during August 2017 in residential gardens of Al-Bonooq district in Baghdad / Iraq.

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