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1. Model-based designof a cone crusher adaptive control system: (Content №6 2025); ... 16. Fu, Y., & Aldrich, C. (2023). Online particle size analysis on conveyor belts with dense convolutional neural networks. Minerals Engineering, 193, 108019. https://doi.org/10.1016/j.mineng.2023.108019 ...; Created on 25 December 2025
2. Empirical comparison of five deep learning architectures for GNSS time-series data forecasting: (Content №5 2025); ... 6. Ige, A. O., & Sibiya, M. (2024). State-of-the-Art in 1D Convolutional Neural Networks: A Survey. IEEE Access, 12, 144082-144105. https://doi.org/10.1109/access.2024.3433513 7. Rizvi, S. M. H. ...; Created on 25 October 2025
3. Determination of bronze БрА7К2О1,5Мц0,3 crystallization interval limit values and phase transformations: (Content №4 2025); ... 4. Farahany, S., Erfani, M., & Karamoozian, A.O. (2010). Artificial Neural Networks to Predict Liquidus Temperature in Hypoeutectic Al-Si Cast Alloys. Journal of Applied Sciences, 10(24), 3243-3249. ...; Created on 26 August 2025
4. Intelligent technology for land cover monitoring due to amber mining on optical satellite images: (Content №3 2025); ... neural networks (CNN + EfficientNet-Edge), and an algorithm for detecting changes over time based on the symmetric difference of changed pixels, which ensures high accuracy and efficiency in the process ...; Created on 25 June 2025
5. Discrete perceptron based on probabilistic estimates of shifted synaptic signals: (Content №2 2025); ... digital processing of discrete signals in the field of artificial neural networks, as well as the formulation of principles for the structural implementation of discrete perceptrons. Methodology. The ...; Created on 26 April 2025
6. Dialogue with generative artificial intelligence: is its “product” free from academic integrity violations?: (Content №2 2025); ... and Leadership, 8(1), 220. https://doi.org/10.61093/bel.8(1).220-233.2024 2. Roba, M., & Moulay, O. K. (2024). Risk management in using artificial neural networks. SocioEconomic Challenges, 8(2), ...; Created on 26 April 2025
7. Research on the effectiveness of using LSTM architecture in modeling the cognitive process of recognition: (Content №1 2025); ... using neural networks. Purpose. Creation and analysis of the bidirectional LSTM neural network architecture for solving the WSD problem in the Ukrainian language. Methodology. One of the modern approaches ...; Created on 25 February 2025
8. Automated student knowledge testing and control system ZELIS: (Content №6 2024); ... 11. Li, J., & Liu, Z. (2019). Multispectral transforms using convolution neural networks for remote sensing multispectral image compression. Remote Sensing, 11, 759-779. https://doi.org/10.3390/rs11070759. ...; Created on 28 December 2024
9. Simulation of the operation modes of the catodic protection complex of pipelines in the approach of overhead power lines: (Content №6 2024); ... neural networks and artificial intelligence. Rudarsko-Geološko-Naftni Zbornik, 38(3), 105-117. https://doi.org/10.17794/rgn.2023.3.9. 20. Dusza, D., & Kosobudzki, G. (2018). Reactive power measurements ...; Created on 28 December 2024
10. Intelligent Sentinel satellite image processing technology for land cover mapping: (Content №5 2024); ... cover mapping using convolutional neural networks. The result will be an image with improved spatial resolution. Methodology. The paper presents a technology using a combination of biquadratic interpolation, ...; Created on 29 October 2024
11. Analysis of natural and man-made factors of landslide development in the Carpathian region using GIS: (Content №5 2024); ... Neural Networks (ANNs), and Multiple Linear Regression (MLR) for Electrical Conductivity Prediction in Aquifers in the Gallikos River Basin, Northern Greece. Hydrology, 8(3), 127. https://doi.org/10.3390/hydrology8030127. ...; Created on 29 October 2024
12. Research on stochastic properties of time series data on chemical analysis of cast iron: (Content №4 2024); ... 19. Khomiak, A. (2022). Methods of time series analysis using recurrent neural networks. Materialy XI Mizhnarodnoi naukovo-praktychnoi konferentsii molodykh uchenykh ta studentiv “Aktualni zadachi suchasnykh ...; Created on 28 August 2024
13. Designing the predictive control of a drum dryer using multi-agent technology: (Content №4 2024); ... Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study. Applied Energy, 165, 60-71. https://doi.org/10.1016/j.apenergy.2015.12.066. ...; Created on 28 August 2024
14. Influence of rock shear processes on the methane content of longwall faces: (Content №4 2024); ... J. (2019). Predicting Methane Concentration in Longwall Regions Using Artificial Neural Networks. International Journal of Environmental Research and Public Health, 16(8), 1406. https://doi.org/10.3390/ijerph16081406. ...; Created on 28 August 2024
15. Current tools to control decarbonization in Ukraine both governmentally and locally: (Content №3 2024); ... 19. Herus, V., & Vitruk, S. (2022). Effectiveness of neural networks in the economy. Scientific Collection “InterConf”, (138), 389-394. Retrieved from https://archive.interconf.center/index.php/conference-proceeding/article/view/2101. ...; Created on 28 June 2024
16. Justification of geodetic monitoring methodology of the retaining walls on the example of the embankment in Kremenchuk: (Content №1 2024); ... Application of the neural networks method in geodetic monitoring of engineering structures. Journal of Kryvyi Rih National University, 51, 8-16. 15. Khailak, A. M. (2016). The using of cluster analysis ...; Created on 29 February 2024
17. Peculiarities of truck transportation in wartime conditions: (Content №6 2023); ... Prohoniuk, I. V. (2018). Methodology of transport and logistics enterprises strategy development modeling on the basis of the neural networks. Collection of scientific papers of the DNURT named after Academician ...; Created on 23 December 2023
18. Data analysis solutions to improve blasting efficiency in mining: (Content №6 2023); ... https://doi.org/10.1109/RTEICT.2016.7807776. 20. Sayadi, A., Monjezi, M., Talebi, N., & Khandelwal, M. (2013). A comparative study on the application of various artificial neural networks to simultaneous ...; Created on 23 December 2023
19. Analysis of the input material flow of the transport conveyor: (Content №5 2023); ... material. The developed generators can be used both for validating existing belt speed control systems and creating new control systems based on neural networks. This opens perspectives for the design ...; Created on 27 October 2023
20. Mineral resource assessment through geostatistical analysis in a phosphate deposit: (Content №5 2023); ... 4. Jalloh, A. B., Kyuro, S., Jalloh, Y., & Barrie, A. K. (2016). Integrating artificial neural networks and geostatistics for optimum 3D geological block modeling in mineral reserve estimation: A ...; Created on 27 October 2023

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