However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...
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: The traditional K-Nearest Neighbor (KNN) algorithm often encounters problems such as weak feature expression ability and poor adaptability to fixed K-values in image classification tasks, ...
To understand and implement the K-Nearest Neighbors (KNN) algorithm for solving classification problems using the Iris dataset. This project demonstrates data preprocessing, model training, evaluation ...
Quantum computing has become a breakthrough in many different research and applied areas. As various authors have demonstrated, the quantum properties have made some computational processes parallel ...
Abstract: The K-Nearest Neighbors (KNN) algorithm is a classical supervised learning method widely used in classification and regression problems. However, the KNN algorithm faces serious challenges ...