Preferred Language
Articles
/
bsj-8819
Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods
...Show More Authors

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of the study is the generated data sets obtained on the basis of theoretical stress relaxation curves. Tables of initial data for training models for all samples are presented, a statistical analysis of the characteristics of the initial data sets is carried out. The total number of numerical experiments for all samples was 346020 variations. When developing the models, CatBoost artificial intelligence methods were used, regularization methods (Weight Decay, Decoupled Weight Decay Regularization, Augmentation) were used to improve the accuracy of the model, and the Z-Score method was used to normalize the data. As a result of the study, intelligent models were developed to determine the rheological parameters of polymers included in the generalized non-linear Maxwell-Gurevich equation (initial relaxation viscosity, velocity modulus) using generated data sets for the EDT-10 epoxy binder as an example. Based on the results of testing the models, the quality of the models was assessed, graphs of forecasts for trainees and test samples, graphs of forecast errors were plotted. Intelligent models are based on the CatBoost algorithm and implemented in the Jupyter Notebook environment in Python. The constructed models have passed the quality assessment according to the following metrics: MAE, MSE, RMSE, MAPE. The maximum value of model error predictions was 0.86 for the MAPE metric, and the minimum value of model error predictions was 0.001 for the MSE metric. Model performance estimates obtained during testing are valid.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Dec 01 2021
Journal Name
Computers & Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
...Show More Authors

View Publication
Crossref (15)
Crossref
Publication Date
Fri Dec 26 2025
Journal Name
Foro De Profesores De Ele(universitat De València)
Study of the difficulties and strategies of learning atonic pronouns in ELE teaching in Iraq
...Show More Authors

The objective of this study is to analyze the difficulties faced by intermediate-level Iraqi students in the use of Spanish unstressed pronouns as a foreign language (ELE). Through a mixed methodology, a descriptive and explanatory analysis was conducted based on written and oral productions of B1-level students at the University of Baghdad.The results show that factors such as interference from the native language (Arabic) and English, as well as grammatical differences between Spanish and Arabic, generate difficulties in the correct use of unstressed pronouns. A contrastive teaching approach is proposed that takes advantage of students' cognitive abilities to highlight similarities and differences between both languages.This stu

... Show More
View Publication Preview PDF
Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Multistage and Numerical Discretization Methods for Estimating Parameters in Nonlinear Linear Ordinary Differential Equations Models.
...Show More Authors

Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Apr 02 2017
Journal Name
Journal Of Educational And Psychological Researches
أثر إستراتيجية التعلم التنافسي في التحصيل لدى طالبات الصف الخامس الأدبي في مادة التربية الإسلامية
...Show More Authors

Aim of the research

The current research is aimed to know the effect of competitive education strategy at the fifth-grade students in the preparatory Islamic Education .

Search procedures

To achieve the goal of research researcher Qsidia chose a middle channel of the daughters of the breeding Baghdad Rusafa , The research sample has been reached (69) student -Bois Qa (34) in the control group , And ( 35) in the experimental group , Researcher Strategy competitive education that was applied to the experimental group were used , the traditional way to the control group .

search result

Search result yielded superiority of the expe

... Show More
View Publication Preview PDF
Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Comparison some of methods wavelet estimation for non parametric regression function with missing response variable at random
...Show More Authors

Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Apr 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Affect of learning the bag in the acquisition of historical concepts for students in the fifth grade literary history
...Show More Authors

The  adopted method in the teaching of history is conservation and indoctrination in all grades, and this will lead to a lack of students interact with teachers in the course of the lesson, and poor use of teachers to questions that raise students' thinking during the lesson, which leads to a lack of interest in the topic of the lesson and wasting opportunities contribution making it the teacher at the center of the educational process, and to provide arrogating the researcher to contribute to teaching style with the belief that the use of this method of teaching could lead to overcome the difficulties and problems faced by the teaching material.

And there are educational complexes integrated approac

... Show More
View Publication Preview PDF
Publication Date
Thu Jan 17 2019
Journal Name
Plant Archives
EFFECT OF ANTI-STRESS ON THE GROWTH AND YIELD OF SWEET AND HOT PEPPERS AND ITS CONTENT OF PEROXIDASE AND IAA
...Show More Authors

MS Elias, RGM AL-helfy, Plant Archives, 2019

View Publication
Scopus (1)
Scopus
Publication Date
Wed Apr 15 2020
Journal Name
Al-mustansiriyah Journal Of Science
Adaptation Proposed Methods for Handling Imbalanced Datasets based on Over-Sampling Technique
...Show More Authors

Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Efficient computational methods for solving the nonlinear initial and boundary value problems
...Show More Authors

Scopus (2)
Crossref (1)
Scopus Crossref
Publication Date
Fri Apr 21 2023
Journal Name
Aip Conference Proceedings
Efficient computational methods for solving the nonlinear initial and boundary value problems
...Show More Authors

In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (1)
Scopus Crossref