• ALGORITHM FOR USING ARTIFICIAL INTELLIGENCE IN PREDICTING FIRE DANGER IN THE SEMEY FOREST IN KAZAKHSTAN 

      Absalyam, Kuanysh; Moldamurat, Khuralay; Hajizadeh, Cengiz (L.N. Gumilyov Eurasian National University, 2025-04-16)
      This article presents an algorithm for using artificial intelligence to predict fire danger in the forests of the Semey region of Kazakhstan. The study analyzes the main factors influencing the occurrence of wildfires, including meteorological parameters (temperature, humidity, wind speed, and atmospheric pressure), as well as the ecological characteristics of the region. ...
      2025-06-05
    • Applying textural Law’s masks to images using machine learning 

      Abdikerimova, Gulzira; Yessenova, Moldir; Yerzhanova, Akbota; Manbetova, Zhanat; Murzabekova, Gulden; Kaibassova, Dinara; Bekbayeva, Roza; Aldashova, Madina (International Journal of Electrical and Computer Engineering, 2023)
      Currently, artificial neural networks are experiencing a rebirth, which is primarily due to the increase in the computing power of modern computers and the emergence of very large training data sets available in global networks. The article considers Laws texture masks as weights for a machinelearning algorithm for clustering aerospace images. The use of Laws texture masks ...
      2024-12-06
    • Applying textural Law’s masks to images using machine learning 

      Abdikerimova, Gulzira; Yessenova, Moldir; Yerzhanova, Akbota; Manbetova, Zhanat; Murzabekova, Gulden; Kaibassova, Dinara; Bekbayeva, Roza; Aldashova, Madina (International Journal of Electrical and Computer Engineering, 2023)
      Currently, artificial neural networks are experiencing a rebirth, which is primarily due to the increase in the computing power of modern computers and the emergence of very large training data sets available in global networks. The article considers Laws texture masks as weights for a machinelearning algorithm for clustering aerospace images. The use of Laws texture masks ...
      2024-11-21
    • Beyond Face Recognition: A Multi-Layered Approach to Academic Integrity in Online Exams 

      Sakhipov, Aivar; Omirzak, Islam; Fedenko, Alexey (Electronic Journal of e-Learning, 2025)
      Ensuring academic integrity in online assessments is crucial for upholding fairness and credibility, especially with the widespread adoption of remote learning. This research addresses key vulnerabilities in preventing cheating and unauthorized collaboration, common in online assessments lacking direct supervision. To address these challenges, an intelligent proctoring ...
      2025-12-17
    • Beyond Face Recognition: A Multi-Layered Approach to Academic Integrity in Online Exams 

      Sakhipov, Aivar; Omirzak, Islam; Fedenko, Alexey (Electronic Journal of e-Learning, 2025)
      Ensuring academic integrity in online assessments is crucial for upholding fairness and credibility, especially with the widespread adoption of remote learning. This research addresses key vulnerabilities in preventing cheating and unauthorized collaboration, common in online assessments lacking direct supervision. To address these challenges, an intelligent proctoring ...
      2026-03-18
    • Classification of pathologies on digital chest radiographs using machine learning methods 

      Aitimov, Murat; Shekerbek, Ainur; Pestunov, Igor; Bakanov, Galitdin; Ostayeva, Aiymkhan; Ziyatbekova, Gulzat; Mediyeva, Saule; Omarova, Gulmira (International Journal of Electrical and Computer Engineering, 2024)
      This article is devoted to the research and development of methods for classifying pathologies on digital chest radiographs using two different machine learning approaches: the eXtreme gradient boosting (XGBoost) algorithm and the deep convolutional neural network residual network (ResNet50). The goal of the study is to develop effective and accurate methods for ...
      2024-12-09
    • Classification of pathologies on digital chest radiographs using machine learning methods 

      Aitimov, Murat; Shekerbek, Ainur; Pestunov, Igor; Bakanov, Galitdin; Ostayeva, Aiymkhan; Ziyatbekova, Gulzat; Mediyeva, Saule; Omarova, Gulmira (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      This article is devoted to the research and development of methods for classifying pathologies on digital chest radiographs using two different machine learning approaches: the eXtreme gradient boosting (XGBoost) algorithm and the deep convolutional neural network residual network (ResNet50). The goal of the study is to develop effective and accurate methods for ...
      2026-03-10
    • Classification of pathologies on digital chest radiographs using machine learning methods 

      Aitimov, Murat; Shekerbek, Ainur; Pestunov, Igor; Bakanov, Galitdin; Ostayeva, Aiymkhan; Ziyatbekova, Gulzat; Mediyeva, Saule; Omarova, Gulmira (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      This article is devoted to the research and development of methods for classifying pathologies on digital chest radiographs using two different machine learning approaches: the eXtreme gradient boosting (XGBoost) algorithm and the deep convolutional neural network residual network (ResNet50). The goal of the study is to develop effective and accurate methods for ...
      2026-03-18
    • Classification of pathologies on digital chest radiographs using machine learning methods 

      Aitimov, Murat; Shekerbek, Ainur; Pestunov, Igor; Bakanov, Galitdin; Ostayeva, Aiymkhan; Ziyatbekova, Gulzat; Mediyeva, Saule; Omarova, Gulmira (International Journal of Electrical and Computer Engineering, 2024)
      This article is devoted to the research and development of methods for classifying pathologies on digital chest radiographs using two different machine learning approaches: the eXtreme gradient boosting (XGBoost) algorithm and the deep convolutional neural network residual network (ResNet50). The goal of the study is to develop effective and accurate methods for automatically ...
      2024-11-22
    • Deep learning based static hand gesture recognition 

      Satybaldina, Dina; Kalymova, Gulzia (Indonesian Journal of Electrical Engineering and Computer Science, 2021)
      Hand gesture recognition becomes a popular topic of deep learning and provides many application fields for bridging the human-computer barrier and has a positive impact on our daily life. The primary idea of our project is a static gesture acquisition from depth camera and to process the input images to train the deep convolutional neural network pre-trained on ImageNet ...
      2024-11-22
    • Deep learning based static hand gesture recognition 

      Satybaldina, Dina; Kalymova, Gulzia (Indonesian Journal of Electrical Engineering and Computer Science, 2021)
      Hand gesture recognition becomes a popular topic of deep learning and provides many application fields for bridging the human-computer barrier and has a positive impact on our daily life. The primary idea of our project is a static gesture acquisition from depth camera and to process the input images to train the deep convolutional neural network pre-trained on ImageNet ...
      2024-12-09
    • Deep learning based static hand gesture recognition 

      Satybaldina, Dina; Kalymova, Gulzia (Indonesian Journal of Electrical Engineering and Computer Science, 2021)
      Hand gesture recognition becomes a popular topic of deep learning and provides many application fields for bridging the human-computer barrier and has a positive impact on our daily life. The primary idea of our project is a static gesture acquisition from depth camera and to process the input images to train the deep convolutional neural network pre-trained on ImageNet ...
      2024-12-17
    • Detection of heart pathology using deep learning methods 

      Naizagarayeva, Akgul; Abdikerimova, Gulzira; Shaikhanova, Aigul; Glazyrina, Natalya; Bekmagambetova, Gulmira; Mutovina, Natalya; Yerzhan, Assel; Tanirbergenov, Adilbek (International Journal of Electrical and Computer Engineering, 2023)
      In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows ...
      2024-12-10
    • Detection of heart pathology using deep learning methods 

      Naizagarayeva, Akgul; Abdikerimova, Gulzira; Shaikhanova, Aigul; Glazyrina, Natalya; Bekmagambetova, Gulmira; Mutovina, Natalya; Yerzhan, Assel; Tanirbergenov, Adilbek (International Journal of Electrical and Computer Engineering, 2023)
      In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to ...
      2024-11-22
    • Development of a decision-making module in the field of real estate rental using machine learning methods 

      Mukhanova, Ayagoz; Baitemirov, Madiyar; Ignatovich, Artyom; Bayegizova, Aigulim; Tanirbergenov, Adilbek; Tynykulova, Assemgul; Bapiyev, Ideyat; Mukhamedrakhimova, Galiya (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      The research is aimed at developing a prototype of a decision support information system for managers of a company operating in the real estate rental industry. The system provides tools for data analysis, the use of mathematical models and expert knowledge to solve complex problems. The work analyzes the practical aspects of the design and use of decision support systems ...
      2026-03-11
    • Development of a decision-making module in the field of real estate rental using machine learning methods 

      Mukhanova, Ayagoz; Baitemirov, Madiyar; Ignatovich, Artyom; Bayegizova, Aigulim; Tanirbergenov, Adilbek; Tynykulova, Assemgul; Bapiyev, Ideyat; Mukhamedrakhimova, Galiya (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      The research is aimed at developing a prototype of a decision support information system for managers of a company operating in the real estate rental industry. The system provides tools for data analysis, the use of mathematical models and expert knowledge to solve complex problems. The work analyzes the practical aspects of the design and use of decision support systems ...
      2026-03-18
    • Development of a hybrid machine learning model for classification of soil types based on geophysical parameters 

      Abzhanova, Ainagul; Taszhurekova, Zhazira; Berlikozha, Bauyrzhan; Kaldarova, Mira; Batyrkhanov, Ardak (International Journal of Innovative Research and Scientific Studies, 2025)
      In this paper, a hybrid model based on RandomForestClassifier and MLPClassifier is presented, achieving an accuracy of 96.07% in the task of soil classification based on geophysical parameters. The results demonstrate the advantages of the proposed approach over selected classical algorithms, indicating a high practical value for precision agriculture and environmental ...
      2026-02-28
    • DEVELOPMENT OF INTELLIGENT ELECTRONIC DOCUMENT MANAGEMENT SYSTEM MODEL BASED ON MACHINE LEARNING METHODS 

      Sambetbayeva, Madina; Kuspanova, Inkarzhan; Yerimbetova, Aigerim; Serikbayeva, Sandugash; Bauyrzhanova, Shynar (Eastern-European Journal of Enterprise Technologies, 2022)
      With the daily increase in document flow, as well as the transition to paperless document management around the world, the demand for electronic document management systems is increasing. This significantly requires optimization of these systems in terms of quality document information retrieval and document management. However, research based on statistical methods cannot ...
      2024-09-20
    • Fire detection using deep learning methods 

      Bayegizova, Aigulim; Abdikerimova, Gulzira; Kaliyeva, Samal; Shaikhanova, Aigul; Shangytbayeva, Gulmira; Sugurova, Laura; Sugur, Zharkynay; Saimanova, Zagira (International Journal of Electrical and Computer Engineering, 2024)
      Fire detection is an important task in the field of safety and emergency prevention. In recent years, deep learning methods have shown high efficiency in solving various computer vision problems, including detecting objects in images. In this paper, monitoring wildfires was considered, which allows you to quickly respond to them and prevent their spread using deep learning ...
      2024-12-10
    • Fire detection using deep learning methods 

      Bayegizova, Aigulim; Abdikerimova, Gulzira; Kaliyeva, Samal; Shaikhanova, Aigul; Shangytbayeva, Gulmira; Sugurova, Laura; Sugur, Zharkynay; Saimanova, Zagira (International Journal of Electrical and Computer Engineering, 2024)
      Fire detection is an important task in the field of safety and emergency prevention. In recent years, deep learning methods have shown high efficiency in solving various computer vision problems, including detecting objects in images. In this paper, monitoring wildfires was considered, which allows you to quickly respond to them and prevent their spread using deep learning methods. ...
      2024-11-25