Preferred Language
Articles
/
joe-1204
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
...Show More Authors

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of each observed distress, the pavement condition surveys were conducted by actually walking through all the sections. Using these data, PCI was calculated utilizing Micro PAVER software. Dynatest Road Surface Profiler (RSP) was used to collect IRI data of all the sections. Using the SPSS software, linear and nonlinear regressions have been used for developing two models between PCI and IRI based on the collected data. These models have the coefficients of determination (R2) equal to 0.715 and 0.722 for linear and quadratic models. Finally, the results indicate the linear and quadratic models are acceptable to predict PCI from IRI directly.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Mon Aug 28 2023
Journal Name
Journal Of Planner And Development
Estimation of urban land price within holly cities by using integrated GIS-regression models: case study Al-Kufa city- Iraq
...Show More Authors

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

... Show More
View Publication Preview PDF
Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
...Show More Authors

View Publication Preview PDF
Scopus (13)
Crossref (12)
Scopus Crossref
Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
...Show More Authors

The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

... Show More
View Publication Preview PDF
Publication Date
Tue Jan 09 2024
Journal Name
مجلة واسط للعلوم الریاضیة
The development of judo from a historical perspective (1880-1980)
...Show More Authors

Judo has witnessed tremendous developments since its inception until the present day. It has been distinguished by its adaptation to the various challenges it has faced throughout the ages. Judo is one of the sports that have been affected by social, technological and cultural changes. These changes reflect its transformation from the traditional Japanese martial art to a global sport practiced. All over the world, therefore, studying the historical development of judo is important, as it provides valuable insights into the development of martial arts over a century, by studying the origins, principles and techniques of judo for the period (1880 - 1980), and also enables us to gain an understanding A deeper understanding of how the art form

... Show More
View Publication
Publication Date
Thu Oct 18 2018
Journal Name
Lambert Academic Publishing
Mathematical Models For Contamination Soil
...Show More Authors

ENGLISH

Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
...Show More Authors

Crossref (11)
Crossref
Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
...Show More Authors

View Publication
Scopus (15)
Crossref (11)
Scopus Clarivate Crossref
Publication Date
Wed Jan 01 2020
Journal Name
Modern Sport
Special exercises according to the Dynafoot data and its effect on the force index and the performance of the front straight air flip skill on the ground movements mat device
...Show More Authors

View Publication
Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
...Show More Authors

 

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

... Show More
View Publication Preview PDF
Crossref (1)
Scopus Crossref
Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
...Show More Authors

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

... Show More
Preview PDF
Crossref (1)
Scopus Crossref