袗胁褌芯褉写褘遥 卸邪褉懈褟谢邪薪褘屑写邪褉褘
Nurakhov, Y.
袘邪褉谢褘覜 卸邪褉懈褟谢邪薪褘屑写邪褉
12
袘械谢褋械薪写褨谢褨泻 卸褘谢写邪褉褘
6
袞邪褉懈褟谢邪薪褘屑 褌爷褉谢械褉褨
3
2026 (2)
2025 (6)
- A Review of Artificial Intelligence and Deep Learning Approaches for Resource Management in Smart Buildings
- A Machine Learning Approach to Investigating Key Performance Factors in 5G Standalone Networks
- IoT-Based Unsupervised Learning for Characterizing Laboratory Operational States to Improve Safety and Sustainability
- Analyzing the Impact of Air Quality on Cognitive Skills Using Machine Learning in a Smart Building Environment
- A Hybrid Machine Learning Approach for High-Accuracy Energy Consumption Prediction Using Indoor Environmental Quality Sensors
- Adaptive Software-Defined Network Control Using Kernel-Based Reinforcement Learning: An Empirical Study