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A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; this is demonstrated by the minimized tracking error and obtained smoothness of the velocity control signal, especially when external disturbances are applied.

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Local and Global Uniqueness Theorems of the N-th Order Partial Differential Equations
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In this paper, we consider inequalities in which the function is an element of n-th partially order space. Local and Global uniqueness theorem of solutions of the n-the order Partial differential equation Obtained which are applications of Gronwall's inequalities.

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Publication Date
Mon Jul 18 2022
Journal Name
International Journal Of Early Childhood Special Education
The effectiveness of a proposed teaching strategy according to The Common Knowledge Construction Model in Mathematical Proficiency for middle school student
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This research aims to know the effectiveness of teaching with a proposed strategy according to the common Knowledge construction modelin mathematical proficiency among students of the second middle class. The researchers adopted the method of the experimental approach, as the experimental design was used for two independent and equal groups with a post-test. The experiment was applied to a sample consisting of (83) students divided into two groups: an experimental comprising (42) students and a control group, the second comprising (41) students., from Badr Shaker Al-Sayyab Intermediate School for Boys, for the first semester of the academic year (2021-2022), the two groups were rewarded in four variables: (chronological age calculated in mo

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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
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Wed Sep 30 2020
Journal Name
College Of Islamic Sciences
The Breadth in the meaning of the "from Surah Maryam as a model.
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Prepositions have a key function, which is to associate parts of a sentence, called letters In addition, it adds the meanings of the verbs to the names, ie reached by them, and called by the coffin characters Qualities..

          I chose to search for the meaning of the preposition "from" in Surat Maryam to know its meanings in terms of originality and expansion, so the title of the research (the meanings of preposition "from" in terms of originality and expansion in Surat Maryam model(

 

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Publication Date
Mon Sep 01 2025
Journal Name
Thermal Science And Engineering Progress
Active mixing strategies for energy-efficient water dispensers: Comparative experimental study of impeller and bubble injection in hot climates
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Mon Jan 01 2018
Journal Name
African Journal Of Hospitality, Tourism And Leisure
An analytical study of the strategic flexibility variation as a function of the dynamic capabilities based on supply chain management (Case study: The General Petroleum Products Distribution Company in Baghdad)
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