Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Nurgul Uzakkyzy
L. N. Gumilyov Eurasian National University
Computer Science & IT Electrical & Electronics Engineering

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Application of informative textural Law’s masks methods for processing space images Moldir Yessenova; Gulzira Abdikerimova; Gulden Murzabekova; Kakabayev Nurbol; Natalya Glazyrina; Saltanat Adikanova; Nurgul Uzakkyzy; Zhanna B. Sadirmekova; Rozamgul Niyazova
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4557-4566

Abstract

Image processing systems are currently used to solve many applied problems. The article is devoted to the identification of negative factors affecting the growth of grain in different periods of harvesting, using a program implemented in the MATLAB software environment, based on aerial photographs. The program is based on the Law’s textural mask method and successive clustering. This paper presents the algorithm of the program and shows the results of image processing by highlighting the uniformity of the image. To solve the problem, the spectral luminance coefficient (SBC), normalized difference vegetation index (NDVI), Law’s textural mask method, and clustering are used. This approach is general and has great potential for identifying objects and territories with different boundary properties on controlled aerial photographs using groups of images of the same surface taken at different vegetation periods. That is, the applicability of sets of Laws texture masks with original image enhancement for the analysis of experimental data on the identification of pest outbreaks is being investigated.
Combined analysis of the importance of factors in agricultural process management tasks Gulzira Abdikerimova; Moldir Yessenova; Aizhan Zharkimbekova; Zhanar Beldeubayeva; Aigulim Bayegizova; Nurgul Uzakkyzy; Ainagul Alimagambetova; Gulden Murzabekova
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.11206

Abstract

The article presents a combined approach for analyzing the significance of factors in the agro-industrial sector using Shapley additive explanations (SHAP), simple combination, and principal component analysis (PCA)+combination methods. The study addresses the pressing need for efficient agricultural resource management under constrained and changing climatic conditions. The proposed methodology evaluates the impact of various factors on key performance indicators such as yield, income, and operating costs. SHAP analysis identified critical determinants, with "Land Area (ha)" contributing significantly to "Market Capacity" (59.5%) and "Sales Revenue" (57.2%), highlighting the importance of production scale. The simple combination method, integrating gradient boosting (GB), mutual information (MI), and recursive feature elimination (RFE) with Lasso, revealed a more balanced factor distribution, assigning 14.5% to "Land Area" and 12.8% and 10.7% to “Seed Use” and “Fertilizer Cost,” respectively. The PCA+combination method emphasized global trends, identifying "Yield per Hectare" (22.5%) and "Field Size" (11.5%) as key contributors to variance. This integrative approach captures localized effects and global interdependencies, offering comprehensive data interpretations. The findings are instrumental in optimizing resource management and strategic planning and enhancing agricultural production efficiency.
Co-Authors Aigulim Bayegizova Ainagul Alimagambetova Aizhan Zharkimbekova Gulden Murzabekova Gulden Murzabekova Gulzira Abdikerimova Kakabayev Nurbol Moldir Yessenova Natalya Glazyrina Rozamgul Niyazova Saltanat Adikanova Zhanar Beldeubayeva Zhanna B. Sadirmekova