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Optimized Artificial Neural network models to time series
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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and the absolute mean square error were also used to measure the accuracy of the estimation for methods used. The important result obtained in this paper is that the optimal neural network was the Backpropagation (BP) and Recurrent neural networks (RNN) to solve time series, whether linear, semilinear, or non-linear. Besides, the result proved that the inefficiency and inaccuracy (failure) of RBF in solving nonlinear time series. However, RBF shows good efficiency in the case of linear or semi-linear time series only. It overcomes the problem of local minimum. The results showed improvements in the modern methods for time series forecasting.

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Selecting Optimum Dimensions for a Three-Phase Horizontal Smart Separator for Khor Mor Gas-Condensate Processing Plant
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      The Khor Mor gas-condensate processing plant in Iraq is currently facing operational challenges due to foaming issues in the sweetening tower caused by high-soluble hydrocarbon liquids entering the tower. The root cause of the problem could be liquid carry-over as the separation vessels within the plant fail to remove liquid droplets from the gas phase. This study employs Aspen HYSYS v.11 software to investigate the performance of the industrial three-phase horizontal separator, Bravo #2, located upstream of the Khor Mor sweetening tower, under both current and future operational conditions. The simulation results, regarding the size distribution of liquid droplets in the gas product and the efficiency gas/liquid separation, r

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Publication Date
Sun Jul 02 2023
Journal Name
Iraqi Journal Of Science
Determination of the Shape and Dimensions of the Sensitive Volume for Solid State Detectors Using Monte Carlo Computer Technique
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In this research the active volume for a number of solid-state detectors of the type of high-purity germanium (HPGe) crystal was evaluated with different radii and depths using scanning method for diagonal (front) and lateral (side). It has been used for this purpose Monte-Carlo efficiency program after its development by adding a subroutine-program for its (subroutine scanning).Also a program has been written to calculate the stopping power and range for incident charged particle on the detector, in order to determine the exact sufficient energy to stop it inside the detector material. The calculations of our results of efficiency were compared with the results of published efficiency and the comparison is very good in terms of improvin

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Transfer Learning Based Traffic Light Detection and Recognition Using CNN Inception-V3 Model
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Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on

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Publication Date
Fri Apr 15 2016
Journal Name
International Journal Of Computer Applications
Hybrid Techniques based Speech Recognition
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Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

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Publication Date
Thu Nov 29 2018
Journal Name
Iraqi Journal Of Science
Improving Extractive Multi-Document Text Summarization Through Multi-Objective Optimization
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Multi-document summarization is an optimization problem demanding optimization of more than one objective function simultaneously. The proposed work regards balancing of the two significant objectives: content coverage and diversity when generating summaries from a collection of text documents.

     Any automatic text summarization system has the challenge of producing high quality summary. Despite the existing efforts on designing and evaluating the performance of many text summarization techniques, their formulations lack the introduction of any model that can give an explicit representation of – coverage and diversity – the two contradictory semantics of any summary. In this work, the design of

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Topological Indices Polynomials of Domination David Derived Networks
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The chemical properties of chemical compounds and their molecular structures are intimately connected. Topological indices are numerical values associated with chemical molecular graphs that help in understanding the physicochemical properties, chemical reactivity and biological activity of a chemical compound. This study obtains some topological properties of second and third dominating David derived (DDD) networks and computes several K Banhatti polynomial of second and third type of DDD.

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Some K-Banhatti Polynomials of First Dominating David Derived Networks
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Chemical compounds, characteristics, and molecular structures are inevitably connected. Topological indices are numerical values connected with chemical molecular graphs that contribute to understanding a chemical compounds physical qualities, chemical reactivity, and biological activity. In this study, we have obtained some topological properties of the first dominating David derived (DDD) networks and computed several K-Banhatti polynomials of the first type of DDD.

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Some Properties of Superplasticized and Retarding Concrete Under Effect of Accelerated Curing Methods
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In recent decades, tremendous success has been achieved in the advancement of chemical admixtures for Portland cement concrete. Most efforts have concentrated on improving the properties of concrete and studying the factors that influence on these properties. Since the compressive strength is considered a valuable property and is invariably a vital element of the structural design, especially high early strength development which can be provide more benefits in concrete production, such as reducing construction time and labor and saving the formwork and energy. As a matter of fact, it is influenced as a most properties of concrete by several factors including water-cement ratio, cement type and curing methods employed.
Because of acce

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Publication Date
Fri Jul 01 2022
Journal Name
Iraqi Journal Of Science
Extractive Multi-Document Text Summarization Using Multi-Objective Evolutionary Algorithm Based Model
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Automatic document summarization technology is evolving and may offer a solution to the problem of information overload. Multi-document summarization is an optimization problem demanding optimizing more than one objective function concurrently. The proposed work considers a balance of two significant objectives: content coverage and diversity while generating a summary from a collection of text documents. Despite the large efforts introduced from several researchers for designing and evaluating performance of many text summarization techniques, their formulations lack the introduction of any model that can give an explicit representation of – coverage and diversity – the two contradictory semantics of any summary. The design of gener

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Publication Date
Mon Jan 13 2020
Journal Name
Day 3 Wed, January 15, 2020
Numerical Simulation of Gas Lift Optimization Using Genetic Algorithm for a Middle East Oil Field: Feasibility Study
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<p>Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t</p> ... Show More
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