Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Publication Date
Sat Feb 01 2020
Journal Name
International Journal Of Computer Science And Mobile Computing
Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
Crime
Crime Prediction
Decision Tree
Logistic Regression
Naïve Bayes
Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin
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(8)
Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Creep-Fatigue Interaction Damage for Polyamide 6,6 Composites
This paper aims to study the damage generated due to creep-fatigue interaction behaviors in solid polyamide 6,6 and its composites that include 1%wt of carbon nanotubes or 30% wt short carbon fiber prepared by an injection technique. The investigation also includes studying the influence of applied temperatures higher than the glass transition temperatures on mechanical properties. The obtained results showed that the addition of reinforcement materials increased all the mechanical properties, while the increase in test temperature reduced all mechanical properties, especially for polyamide 6,6. The creep-fatigue interaction resistance also improved due to the addition of reinforcement materials by inc
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Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p>
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Feature selection
COVID 19
Recursive Feature Elimination
Extra Tree Classifier
Restricted Boltzmann Machine
Naïve Bayesian
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(24)
Publication Date
Tue Mar 20 2018
Journal Name
Offshore Technology Conference Asia
Prediction of Hydrate Phase Equilibrium Conditions for Different Gas Mixtures
Abstract<p>Gas hydrate formation poses a significant threat to the production, processing, and transportation of natural gas. Accurate predictions of gas hydrate equilibrium conditions are essential for designing the gas production systems at safe operating conditions and mitigating the problems caused by hydrates formation. A new hydrate correlation for predicting gas hydrate equilibrium conditions was obtained for different gas mixtures containing methane, nitrogen and carbon dioxide. The new correlation is proposed for a pressure range of 1.7-330 MPa, a temperature range of 273-320 K, and for gas mixtures with specific gravity range of 0.553 to 1. The nonlinear regression technique was applie</p>
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new correlation
hydrate equilibrium temperature
correlation
prediction
gas mixture
hammerschmidt
phase equilibria
artificial intelligence
upstream oil & gas
hydrate
(7)
Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Development prediction algorithm of vehicle travel time based traffic data
Prediction Algorithm
Travel Times
Universal Transverse Mercator (UTM)
Polygon of
Traffic Data
This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera
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(1)
Publication Date
Sun Jun 08 2025
Journal Name
J Nat Sc Biol Med
Publication Date
Sun Jun 08 2025
Journal Name
Journal Of Natural Science, Biology And Medicine
Publication Date
Fri Jul 19 2024
Journal Name
Baghdad Science Journal
An Analytical Comparison of the Behavior of Machine Learning and Deep Learning in Stock Market Prediction
Stock market prediction
Machine learning
Deep learning
Recurrent neural network
LSTM
J48
Logistic regression
Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec
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