Search - Науковий вісник НГУ

1. Analysis of mathematical methods for describing financial flows: dynamic modeling of an innovative company: (Content №5 2024); ... H., Creamer, G. G., & Rafizadeh, N. (2019). Machine learning in energy economics and finance: A review. Energy Economics, 81, 709-727. https://doi.org/10.1016/j.eneco.2019.05.006. 2. Pang, X., Zhou, ...; Created on 29 October 2024
2. Innovation and infrastructure: driving forces for entrepreneurship development and economic opportunities: (Content №5 2024); ... via the Sherwood principle and machine learning. Resources, Conservation and Recycling, 167, 105232. https://doi.org/10.1016/j.resconrec.2020.105232. 6. Tepliuk, M., Fomenko, B., Sahaidak, M., Petrishyna, ...; Created on 29 October 2024
3. Analysis of natural and man-made factors of landslide development in the Carpathian region using GIS: (Content №5 2024); ... 14. Arabameri, A., Chandra, Pal S., Rezaie, F., Chakrabortty, R., Saha, A., Blaschke, T., Di Napoli, M., …, & Ngo, T. (2021). Decision tree based ensemble machine learning approaches for landslide ...; Created on 29 October 2024
4. Research on stochastic properties of time series data on chemical analysis of cast iron: (Content №4 2024); ... of financial asset price forecasting models using machine learning methods and statistical analysis. UKRNOIVI. 13. Zamula, O. A. (2019). Optimization of discrete complex signal synthesis methods in modern ...; Created on 28 August 2024
5. Features of the assessment of occupational risks under hazardous working conditions: (Content №4 2024); ... Learning about risk: Machine learning for risk assessment. Safety Science, 118, 475-486. https://doi.org/10.1016/j.ssci.2019.06.001. 22. Bazaluk, O., Tsopa, V., Cheberiachko, S., Deryugin, O., Radchuk, ...; Created on 28 August 2024
6. Improvement of the method for optimization of predicting the efficiency of a robotic platform: (Content №3 2024); ... in regression models from machine learning. These acquired models are employed for predicting the efficiency of a specific configuration of a robotic platform designed to perform particular practical tasks. ...; Created on 28 June 2024
7. Drilling wells taking into account the dynamic properties of rocks: (Content №2 2024); ... 5. Hazbeh, O., Khezerloo-ye Aghdam, S., Ghorbani, H., Mohamadian, N., Ahmadi Alvar, M., & Moghadasi, J. (2020). Comparison of accuracy and computational performance between the machine learning algorithms ...; Created on 01 May 2024
8. Modeling the return on investment in human capital in the IT industry of Ukraine: (Content №1 2024); ... 437-461. https://doi.org/10.1287/isre.2020.0975. 16. Jaisawal, R. (2022). Machine Learning to Evaluate Important Human Capital (HC) Determinants Impacting IT Compensation. Ramanujan International Journal ...; Created on 29 February 2024
9. An overview of hydrogen production via reforming from natural gas: (Content №1 2024); ... on process modelling and machine learning within hydrogen production with carbon capture. Gas Science and Engineering, 118, 205104. https://doi.org/10.1016/j.jgsce.2023.205104. 60. Yu, X., Shen, Y., ...; Created on 29 February 2024
10. Automated building damage detection on digital imagery using machine learning: (Content №6 2023); ... 134 - 140 https://doi.org/10.33271/nvngu/2023-6/134 Abstract: Purpose. To develop an automated method based on machine learning for accurate detection of features of a damaged building on digital imagery. ...; Created on 23 December 2023
11. Analysis and prediction of surface settlements during the digging of underground mining works (Algeria): (Content №6 2023); ... 8. Mbarak, W. K., Cinicioglu, E. N., & Cinicioglu, O. (2020). SPT based determination of undrained shear strength: Regression models and machine learning. Frontiers of Structural and Civil Engineering, ...; Created on 23 December 2023
12. Shaping sustainable strategies of freight forwarding companies in the environment of the road transport market: (Content №5 2023); ... K., Nizamis, A., Ioannidis, Dimosthenis K., & Tzovaras, D. (2023). Utilizing machine learning on freight transportation and logistics applications: A review. ICT Express, 9(3), 284-295. https://doi.org/10.1016/j.icte.2022.02.001. ...; Created on 27 October 2023
13. Mineral resource assessment through geostatistical analysis in a phosphate deposit: (Content №5 2023); ... models for the studied variables. The model selection is done by applying a cross-validation procedure leave-one-out (LOOCV). LOOCV is a resampling technique used in statistical analysis and machine learning ...; Created on 27 October 2023
14. Investigation of combined ensemble methods for diagnostics of the quality of interaction of human-machine systems: (Content №4 2023); ... 3. Belitz, K., & Stackelberg, P. E. (2021). Evaluation of six methods for correcting bias in estimates from ensemble tree machine learning regression models. Environmental Modelling & Software, ...; Created on 28 August 2023
15. Improving a process of managing dynamic occupational risks: (Content №4 2023); ... https://doi.org/10.1016/j.ssci.2022.106050. 16. Paltrinieri, N., Comfort, L., & Reniers, G. (2019). Learning about risk: Machine learning for risk assessment. Safety Science, 118, 475-486. https://doi.org/10.1016/j.ssci.2019.06.001. ...; Created on 28 August 2023
16. Evaluation and control of data relevance in information systems of the transport industry management: (Content №3 2023); ... M. L., & Rohde, W. (2021). Digital Twin Framework for Machine Learning-Enabled Integrated Production and Logistics Processes, (pp. 218-227). In Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, ...; Created on 27 June 2023
17. Influence of Industry 4.0 on strategies of companies entering the global market of data integration services: (Content №2 2023); Authors: T.Tsygankova, orcid.org/0000-0001-6177-2555, Kyiv National Economic University named after Vadym Hetman, Kyiv, Ukraine O.Yatsenko*, orcid.org/0000-0003-4399-2217, Kyiv National Economic University ...; Created on 28 April 2023
18. Peculiarities of thermomodernization of the heating system of military infrastructure complexes: (Content №2 2023); ... A., Moustakidis, S., & Karcanias, N. (2021). Machine learning applied on the district heating and cooling sector: a review. Energy Systems, 1, 1-30. https://doi.org/10.1007/s12667-020-00405-9. 15. ...; Created on 28 April 2023
19. Predicting underground mining impact on the earth’s surface: (Content №1 2023); ... properties in karaganda territory using machine learning methods. Bulletin of the Tomsk Polytechnic University, Geo Assets Engineering, 333(2), 204-210. https://doi.org/10.18799/24131830/2022/2/3358. 21. ...; Created on 25 February 2023
20. Influence of misalignment of connection of electrical machine shafts on the nature of electric power of the induction motor: (Content №6 2022); ... storage system using fuzzy logic controllers. AI and Machine Learning Paradigms for Health Monitoring System, 86, 339-349. https://doi.org/10.1007/978-981-33-4412-9_20. 14. Shreyner, R., Kalygin, A., & ...; Created on 25 December 2022

Start
Prev
1
2
Next
End

Науковий вісник НГУ

Archive

Most read

NEW ON THE SITE

Visitors

Guest Book

Registration data

Contacts