Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Adikanova, Saltanat
Unknown Affiliation
Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Ontological model of the process of intensification of teachers’ competencies Bazarova, Madina; Alibekkyzy, Karlygash; Adikanova, Saltanat; Bugubayeva, Alina; Zhomartkyzy, Gulnaz; Jaxalykova, Akmaral; Baidildina, Aizhan; Keribayeva, Talshyn
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp446-458

Abstract

Currently, there is a need to improve the education system and develop interdisciplinary research at all levels of education, from school to postgraduate education. The introduction of interdisciplinary connections contributes to the formation of a holistic understanding of natural phenomena and the connections between them. Thus, this knowledge becomes more meaningful and applicable in practice. This article proposes a conceptual model of the content of education in the form of a thesaurus and ontology. The use of these models will allow you to adaptively select and systematize educational information. The article also discusses the possibilities and experience of using ontological modeling and engineering for the conceptual description of school and higher education. In addition, the article discusses the development of an ontological model of the process of expanding teachers’ competencies with the integration of science, technology, engineering and mathematics (STEM) education. The use of ontological engineering methods will improve the quality of teacher education through the semantic description of knowledge in the subject area and the use of interdisciplinary and STEM approaches in the educational process. 
Assessing external factors of the agro-industrial complex efficiency based on data Mauina, Gulalem; Aitimova, Ulzada; Kadyrova, Ainagul; Adikanova, Saltanat; Syzdykpayeva, Aigul; Seitakhmetova, Zhanat; Alimagambetova, Ainagul; Shekerbek, Ainur
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.10459

Abstract

Modern agriculture faces the challenge of increasing production efficiency in the context of limited resources and variable climatic conditions. This article presents an approach to assessing the impact of various factors on agro-industrial indicators using machine learning methods. The primary focus is on the development and application of a hybrid analysis that includes techniques such as gradient boosting (GB), mutual information (MI), and recursive feature elimination (RFE). The study was conducted using data from agro-industrial enterprises in the North Kazakhstan region for the period 2020–2022, encompassing production, climatic, and economic indicators. It was found that crop area, average crop weight, and precipitation are the most significant factors, accounting for up to 93% of the correlation with yield increase. The use of the proposed methods made it possible to reduce forecast uncertainty by 28% and increase the accuracy of key indicator predictions by 15–20%. The results of the analysis, visualized as correlation matrices and feature significance maps, confirm the possibility of applying the proposed approach to optimize the management of agro-industrial production. The application of the developed methodology contributes to the development of strategies aimed at the sustainable development of the agro-industrial complex.
Co-Authors Aitimova, Ulzada Alibekkyzy, Karlygash Alimagambetova, Ainagul Baidildina, Aizhan Bazarova, Madina Bugubayeva, Alina Jaxalykova, Akmaral Kadyrova, Ainagul Keribayeva, Talshyn Mauina, Gulalem Seitakhmetova, Zhanat Shekerbek, Ainur Syzdykpayeva, Aigul Zhomartkyzy, Gulnaz