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Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the multiple discriminant model (MDM) and neural network model (NNM). Zublin trunk sewer in Baghdad city was selected as a case study. The deterioration model based on the NNDM provide the highest overall prediction efficiency which could be attributed to its inherent ability to model complex processes. The MDDM provided relatively low overall prediction efficiency, this may be due to the restrictive assumptions by this model. For the NNDM the confusion matrix gave overall prediction efficiency about 87.3% for model training and 70% for model validation, and the overall conclusion from these models may predict that Zublin trunk sewer is of a poor condition.

Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between the logistic regression model and Linear Discriminant analysis using Principal Component unemployment data for the province of Baghdad
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     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Analysis of a harvested discrete-time biological models
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This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.

Scopus (6)
Scopus
Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Computer Model Application for Sorting and Grading Citrus Aurantium Using Image Processing and Artificial Neural Network
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Abstract<p>This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin</p> ... Show More
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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Rooting non-violence in the Holy Quran And models of the Prophet application
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The term “non-violence” is a means of political, social, and advocacy that excludes force in reaching its objectives, and lacks infringement of the rights of non-violence. The policy of non-violence is a beautiful logic of the whole of Islamic creation, in that it is an integral part of the whole structure of Islam and it is a policy of brilliant and brilliant saying in the Almighty: `` Neither level nor good or bad, pay what is better, If that between you and him enmity as if he were intimate guardian (Suratvsalat, verse: 34. Has According to the prophet of Islam, it means that God gives to kindness (kindness) what does not give to violence (Sunan Abu Dawood, 4/255). These terms accurately communicate what is meant by violence and n

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Publication Date
Tue Jun 15 2021
Journal Name
Al-academy
Consistency and Consistency in Contemporary Iraqi Painting - Selected Models-: حسين شاكر قاسم العيداني
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  The tagged research is concerned with observation and investigating the concepts of consistency and harmony in contemporary Iraqi painting (selected models) in order to reveal the mechanisms and rules of these two concepts in the artistic field and their mechanisms of operation. How reflected tools Consistency and harmony in contemporary Iraqi painting? What is consistency and what are its mechanisms and principles? Is consistency a unit product quality? Are there similarities between consistency and harmony? What is harmony and its principles and rules? As for the second chapter, it included two topics that dealt with the first topic - consistency and harmony between concept and significance, while the second topic meant - histor

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Crossref
Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Fri Jun 05 2026
Journal Name
Imam Ja&#39;afar Al-sadiq University Journal Of Legal Studies
The role of fluctuations and crises in stock markets in activating market makers models
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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and

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