Results 31 to 40 of about 2,607,610 (251)
Frontiers in Earth Science, 2021 Near surface air temperature (NSAT) is one of the most important climatic parameters and its variability plays a vital role in natural processes associated with climate.
Jia Zhou, Jia Zhou, Tao Lu
doaj +1 more source
Online change-point detection with kernels
Pattern Recognition, 2023 Change-points in time series data are usually defined as the time instants at which changes in their properties occur. Detecting change-points is critical in a number of applications as diverse as detecting credit card and insurance frauds, or intrusions into networks. Recently the authors introduced an online kernel-based change-point detection method
Ferrari, André +3 more
openaire +4 more sources
Axioms, 2022 Overseas students constitute the paramount talent resource for China, and, hence, overseas talent mobility prediction is crucial for the formulation of China’s talent strategy.
Peng Jiang +4 more
doaj +1 more source
Hierarchical Spatio-Temporal Change-Point Detection
The American Statistician, 2023 Detecting change-points in multivariate settings is usually carried out by analyzing all marginals either independently, via univariate methods, or jointly, through multivariate approaches. The former discards any inherent dependencies between different marginals and the latter may suffer from domination/masking among different change-points of ...
Mehdi Moradi +3 more
openaire +3 more sources
Safety, 2020 Trends and underlying patterns should be identified in the timely distribution of road traffic offenses to increase traffic safety. In this study, a time series analysis was used to study the incidence rate of road traffic violations on Iranian rural ...
Milad Delavary +2 more
doaj +1 more source
Semantic supported urban change detection using ALS point clouds
International Journal of Applied Earth Observations and Geoinformation, 2023 Airborne laser scanning (ALS) has experienced significant development and boosted widespread applications over the recent years. With increasing data quality and acquisition convenience, multi-temporal ALS point clouds have been used for change detection
Li Fang +4 more
doaj +1 more source
Random Forests for Change Point Detection
, 2022 Journal of Machine Learning Research, 24 (216)
Londschien, Malte +2 more
openaire +5 more sources
Statistical Theory and Related Fields, 2021 The multi-armed bandit (MAB) problem studies the sequential decision making in the presence of uncertainty and partial feedback on rewards. Its name comes from imagining a gambler at a row of slot machines who needs to decide the best strategy on the ...
Yaping Wang +3 more
doaj +1 more source
Three Dimensional Change Detection Using Point Clouds: A Review
Geomatics, 2022 Change detection is an important step for the characterization of object dynamics at the earth’s surface. In multi-temporal point clouds, the main challenge is to detect true changes at different granularities in a scene subject to significant noise and ...
Abderrazzaq Kharroubi +4 more
doaj +1 more source
DETECTING UNKNOWN CHANGE POINTS FOR HETEROSKEDASTIC DATA
Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, 2023 There are several tests to detect structural change at unknown change points. The Andrews Sup F test (1993) is the most powerful, but it requires the assumption of homoskedasticity. Ahmed et al. (2017) introduced the Sup MZ test, which relaxes this assumption and tests for changes in both the coefficients of regression and variance simultaneously.
Sıdıka Başçı, Asad Ul Islam Khan
openaire +3 more sources