Preferred Language
Articles
/
5BdBP48BVTCNdQwCr2WX
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
...Show More Authors

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning models for a variety of tasks under the control of a unified architecture for each proposed model.

Scopus Crossref
View Publication
Publication Date
Wed Oct 03 2018
Journal Name
Opcion
Evaluating the financial performance according to the traditional and modern financial indicators
...Show More Authors

The research aims to develop the general performance and improve the level of activity of private insurance companies in line with the current progress of the country. Besides, Evaluating financial performance to diagnose weaknesses and strengths in sample research companies and then developing appropriate solutions. The deviation in the financial performance of the research sample was revealed by measuring the various accounts of the company. The research sample included five companies in the private insurance sector listed in the Iraqi Stock Exchange Market, which represent the private insurance sector. The research concluded that the added economic value is a broad concept that goes beyond the traditional performance evaluation process a

... Show More
Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Comparison of Faster R-CNN and YOLOv5 for Overlapping Objects Recognition
...Show More Authors

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

... Show More
View Publication Preview PDF
Scopus (12)
Crossref (8)
Scopus Crossref
Publication Date
Thu Nov 09 2023
Journal Name
Journal Of Global Scientific Research In Business Management And Economics
The profitability index and its role in evaluating the performance of specialized banks in Iraq.
...Show More Authors

Central banks around the world typically use various financial indicators to evaluate performance. In Iraq, the indicators used by central banks to evaluate the performance of banks are of great importance to ensure that the banks operating within the Iraqi banking system comply with the regulatory and legal requirements issued by the Central Bank of Iraq or the Ministry of Finance. Given the need to study the profitability indicator to ensure its ability to evaluate the performance of specialized banks in Iraq, these banks carry out their banking activities and businesses through capital funded by the government. The use of profitability indicators in evaluating the performance of specialized banks provides information about the profitabil

... Show More
View Publication Preview PDF
Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
...Show More Authors

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

... Show More
View Publication
Scopus (9)
Crossref (6)
Scopus Crossref
Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Administrative control procedures and their relation to evaluating the job performance: in the companies department
...Show More Authors

The study sought to highlight the importance of applying the administrative control procedures which play an important role in assessing the performance of the employees of the tax administration and specifically the companies department by setting the standards and objectives of the department on the basis of which in the implementation of its work and identify deviations and errors and find appropriate solutions and evaluate the results according to appropriate solutions, The study of the problem of research, namely the extent to which the tax administration applied to the administrative control procedures in view of its importance in evaluating the performance of its employees and the extent of their application to the legislations an

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 08 2023
Journal Name
International Journal Of Research In Social Sciences And Humanities
Evaluating Banking Performance According to the European Model of Institutional Excellence: Case Study at United Bank for Investment and Finance1
...Show More Authors

The aim of the research is to identify the impact of the dimensions of the European Excellence Model in evaluating the performance of the bank of the research sample, as well as to interpret which dimensions are more important to the banks of the research sample. Based on the dimensions of this model, the United Bank for Investment and Finance has chosen a research community, and has met with officials of the United Bank for Investment and Finance at various administrative levels to measure the practices of excellence management in the European model, and the analytical approach has been the case study and the construction of the checklist as a tool to collect information. The research has reached the most important results There is a discr

... Show More
View Publication
Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
...Show More Authors
Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
Scopus (6)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
...Show More Authors

The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sci.
Evaluating the performance of introduced varieties of Maize (Zea mays L.) And estimating some genetic parameters
...Show More Authors

Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Statistical
Evaluating the performance of introduced varieties of maize (Zea Mays L.) and estimating some genetic parameters
...Show More Authors

Scopus (11)
Scopus