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joe-2227
Optimized Zero and First Order Design of Micro Geodetic Networks
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Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applied to three cases of selected network to analyzed using the objective function of A-Optimality and D-Optimality, with selected range of movement of 300m to each point in each direction. The first case was a free network, the second case was with P55 and P73 as control points, and the third case was with P42 and P44 as control points. The results showed that the third case was the optimal design with high precision

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Fri Nov 01 2024
Journal Name
Process Safety And Environmental Protection
Optimized ensemble deep random vector functional link with nature inspired algorithm and boruta feature selection: Multi-site intelligent model for air quality index forecasting
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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
An Efficient Numerical Method for Solving Volterra-Fredholm Integro-Differential Equations of Fractional Order by Using Shifted Jacobi-Spectral Collocation Method
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The aim of this article is to solve the Volterra-Fredholm integro-differential equations of fractional order numerically by using the shifted Jacobi polynomial collocation method. The Jacobi polynomial and collocation method properties are presented. This technique is used to convert the problem into the solution of linear algebraic equations. The fractional derivatives are considered in the Caputo sense. Numerical examples are given to show the accuracy and reliability of the proposed technique.

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Publication Date
Mon Jul 25 2022
Journal Name
2022 Ieee 20th International Conference On Industrial Informatics (indin)
Robust Continuous Sliding Mode Controller for Uncertain Canonical Brunovsky Systems Using Reduced Order Extended State Observer
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A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its esti

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Sun Jun 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
FIRST RECORD OF OPILIO KAKUNINI SNEGOVAYA, COKENDOLPHER & MOZAFFARIAN, 2018 (ARACHNIDA, OPILIONES, PHALANGIIDAE) FROM IRAQ
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The species of Opilio kakunini Snegovaya, Cokendolpher & Mozaffarian, 2018 was recorded for the first time in Iraq; as well as to four species belonging to this order which were recorded previously. In this paper, we added a new species to the checklist of Iraqi opilionid fauna with a description of the most important characteristics, along with genitalia, for both males and females are presented with digital photographs. Specimens of males and females were collected from Al- Rifai district northern of Dhi-Qar Province, southern of Iraq.
 

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
Social Studies Teachers' Perceptions of the Importance of Employing Twenty-First Century Skills in Teaching
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The study aimed to identify the perceptions of social studies teachers in the Governorate of Muscat about the importance of employing the skills of the twenty-first century in teaching. The study employed a qualitative approach. The two researchers used an analytical approach based on the Grounded Theory, the data was gathered through semi-structured interviews with (15) male and female teachers. The results indicated that social studies teachers relate the twenty-first-century skills more to improving students’ achievement level in the subject, while they see that these skills have less influence in developing students’ communication skills and cooperation with their peers. In light of the results of the study, the two researchers r

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Publication Date
Sun Dec 15 2019
Journal Name
Al-academy
Organism and its Aesthetic Connections in the Interior Design: حسنين صباح داوّد سلمان
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Organism is considered one of the intellectual products that search for compatibility and harmony with the natural environment. Man has adopted on since the ancient times in choosing his residence through imitating nature such as animal burrows, hives, bird nests and others of the natural manifestations being spontaneous inspirations. With the development of the age, these concepts turned into an analysis that examines the philosophy that deals with the shapes and functions of various elements in the nature as a source of inspiration, and discusses the call for contemplation and achieving benefits physically and spiritually in line with the nature of the organic thought that seeks to keep up with modern technologies that are characterize

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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