Results 31 to 40 of about 592,656 (330)

Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier

Remote Sensing, 2020
Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we propose a new flood susceptibility mapping technique. We employ new ensemble models based on bagging as a meta-classifier and K-Nearest Neighbor (KNN) coarse ...
H. Shahabi, A. Shirzadi, K. Ghaderi, E. Omidvar, N. Al‐Ansari, J. Clague, M. Geertsema, K. Khosravi, A. Amini, Sepideh Bahrami, Omid Rahmati, K. Habibi, A. Mohammadi, Hoang Nguyen, A. Melesse, B. Ahmad, A. Ahmad   +16 more
semanticscholar   +1 more source

Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery

Italian National Conference on Sensors, 2017
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost classifiers at producing high accuracies. However, only a few studies have
Phan Thanh Noi, M. Kappas
semanticscholar   +1 more source

ALGORITMA K-NEAREST NEIGHBOR TERHADAP PELUANG MAHASISWA MENJADI AKTIVIS KAMPUS PADA JURUSAN MATEMATIKA UNIVERSITAS NEGERI PADANG

Jurnal Lebesgue, 2023
The purpose of this study was to predict whether mathematics students at Padang State University have the opportunity to become campus activists using the K-Nearest Neighbor Algorithm (KNN). This research will be used as a benchmark to calculate how many
Muhammad Fadhli Gusvino, Defri Ahmad
doaj   +1 more source

Reverse k Nearest Neighbor Search over Trajectories [PDF]

, 2017
GPS enables mobile devices to continuously provide new opportunities to improve our daily lives. For example, the data collected in applications created by Uber or Public Transport Authorities can be used to plan transportation routes, estimate ...
Bao, Zhifeng, Cong, Gao, Culpepper, J. Shane, Sellis, Timos, Wang, Sheng   +4 more
core   +1 more source

Random k conditional nearest neighbor for high-dimensional data [PDF]

PeerJ Computer Science
The k nearest neighbor (kNN) approach is a simple and effective algorithm for classification and a number of variants have been proposed based on the kNN algorithm. One of the limitations of kNN is that the method may be less effective when data contains
Jiaxuan Lu, Hyukjun Gweon
doaj   +2 more sources

Bridging frustrated-spin-chain and spin-ladder physics: quasi-one-dimensional magnetism of BiCu2PO6 [PDF]

, 2010
We derive and investigate the microscopic model of the quantum magnet BiCu2PO6 using band structure calculations, magnetic susceptibility and high-field magnetization measurements, as well as ED and DMRG techniques.
Alexander A. Tsirlin, Andreas M. Läuchli, Christoph Geibel, Deepa Kasinathan, F. Abraham, Franziska Weickert, Helge Rosner, Ioannis Rousochatzakis, J. B. Goodenough, Oleg Janson, Ramesh Nath   +10 more
core   +2 more sources

Effects of Distance Measure Choice on K-Nearest Neighbor Classifier Performance: A Review [PDF]

Big Data, 2017
The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers, yet its performance competes with the most complex classifiers in the literature.
V. B. Surya Prasath, Haneen Arafat Abu Alfeilat, Omar Lasassmeh, Ahmad Hassanat   +3 more
semanticscholar   +1 more source

Lip language identification via Wavelet entropy and K-nearest neighbor algorithm

EAI Endorsed Transactions on e-Learning, 2021
INTRODUCTION: Image processing technology is widely used in lip recognition, which can automatically detect and analyse the unstable shape of human lips.
Ran Wang, Yifan Cui, Xinyu Gao, Wei Chen, Mingbo Hu, Qian Li, Jiahui Wei, XianWei Jiang   +7 more
doaj   +1 more source

Network intrusion detection based on random k-nearest neighbor ensemble algorithm

Nantong Daxue xuebao. Ziran kexue ban, 2023
To improve the accuracy and generalization of network intrusion detection models, a model based on the random k-nearest neighbor(k-NN) ensemble algorithm is proposed for network flow intrusion detection.
ZHANG Chengye; LI Zhuoxuan; CAO Jinde
doaj   +1 more source

Two-Pass K Nearest Neighbor Search for Feature Tracking

IEEE Access, 2018
In recent years, feature tracking has become one of the most important research topics in computer vision. Many efforts have been made to design excellent feature matching methods. For large-scale structure from motion, however, existing feature tracking
Mingwei Cao, Wei Jia, Zhihan Lv, Wenjun Xie, Liping Zheng, Xiaoping Liu   +5 more
doaj   +1 more source