The battlefield is no longer just a physical space of troops and artillery; it is a vast, invisible network of data, sensors, and machine learning models. In the current Iran-Israel conflict, AI is ...
The use of machine learning (ML) and artificial intelligence (AI) in power converters represents the latest development in ...
Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...
Traditional lending relies on collateral and a financial history that productive smallholder farmers may find difficult to ...
Abstract: The random forest algorithm was applied to the dry slag discharge control system in power plants to enable intelligent control of thermal slag transportation, discharge, and damper ...
How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by York University has found that not only could machine-learning models ...
Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...
1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
Abstract: Decision tree-based random forest algorithms can efficiently process multi-source heterogeneous data, accurately predict complex hydrological processes, and optimize power plant operation ...
A Python implementation of the Truly Spatial Random Forests (SRF) algorithm for geoscience data analysis. Based on: Talebi, H., Peeters, L.J.M., Otto, A. & Tolosana-Delgado, R. (2022). A Truly Spatial ...
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