Anomaly Detection in Smart Environments: A Comprehensive Survey
IEEE Access,
Год журнала:
2024,
Номер
12, С. 64006 - 64049
Опубликована: Янв. 1, 2024
Anomaly
detection
is
a
critical
task
in
ensuring
the
security
and
safety
of
infrastructure
individuals
smart
environments.This
paper
provides
comprehensive
analysis
recent
anomaly
solutions
data
streams
supporting
environments,
with
specific
focus
on
multivariate
time
series
various
such
as
home,
transport,
industry.The
aim
to
offer
thorough
overview
current
state-of-the-art
techniques
applicable
these
includes
an
examination
publicly
available
datasets
suitable
for
developing
techniques.The
survey
designed
inform
future
research
practical
applications
field,
serving
valuable
resource
researchers
practitioners.It
not
only
reviews
range
methods,
from
statistical
proximity-based
those
adopting
deep
learning-methods
but
also
covers
fundamental
aspects
detection.These
include
categorization
anomalies,
scenarios,
challenges
associated,
evaluation
metrics
assessing
techniques'
performance.
Язык: Английский
A simple rapid sample-based clustering for large-scale data
Engineering Applications of Artificial Intelligence,
Год журнала:
2024,
Номер
133, С. 108551 - 108551
Опубликована: Май 11, 2024
Язык: Английский
Escape velocity-based adaptive outlier detection algorithm
Knowledge-Based Systems,
Год журнала:
2025,
Номер
311, С. 113116 - 113116
Опубликована: Фев. 1, 2025
Язык: Английский
Rectifying inaccurate unsupervised learning for robust time series anomaly detection
Information Sciences,
Год журнала:
2024,
Номер
662, С. 120222 - 120222
Опубликована: Янв. 29, 2024
Язык: Английский
Edge conditional node update graph neural network for multivariate time series anomaly detection
Information Sciences,
Год журнала:
2024,
Номер
679, С. 121062 - 121062
Опубликована: Июнь 21, 2024
Язык: Английский
Adaptive gravitational clustering algorithm integrated with noise detection
Expert Systems with Applications,
Год журнала:
2024,
Номер
unknown, С. 125733 - 125733
Опубликована: Ноя. 1, 2024
Язык: Английский
Machine learning models with innovative outlier detection techniques for predicting heavy metal contamination in soils
Journal of Hazardous Materials,
Год журнала:
2024,
Номер
481, С. 136536 - 136536
Опубликована: Ноя. 19, 2024
Язык: Английский
Deep Anomaly Detection: A Linear One-Class SVM Approach for High-Dimensional and Large-Scale Data
K. Suresh,
K. Jayasakthi Velmurugan,
R.G. Vidhya
и другие.
Applied Soft Computing,
Год журнала:
2024,
Номер
167, С. 112369 - 112369
Опубликована: Окт. 24, 2024
Язык: Английский
面向光学遥感卫星星上定位精度优化的轻量化矢量控制库技术
李明 Li Ming,
董杨 Dong Yang,
范大昭 Fan Dazhao
и другие.
Acta Optica Sinica,
Год журнала:
2024,
Номер
44(6), С. 0628003 - 0628003
Опубликована: Янв. 1, 2024
针对当前光学智能遥感卫星有限存储能力对全球控制信息的轻量化需求,提出一种面向光学遥感卫星星上定位精度优化的轻量化矢量控制库技术。首先,在地面提取完整道路网,通过道路细化、节点提取以及拓扑关系构建等处理,生成星上轻量化矢量控制库并上注卫星;其次,星上在轨提取道路结构,并利用随机游走避免道路缺失的影响,生成随机游走矢量结构;然后,引入隐马尔科夫模型,搜索对应矢量,并设计分层匹配策略以精化匹配结果,实现星上轻量化矢量控制库与随机游走矢量结构的匹配;最后,利用不同类型卫星影像进行随机游走矢量结构提取、星上矢量匹配以及定位性能分析。结果表明,所提光学遥感卫星的星上轻量化矢量控制库能够有效改善非量测光学遥感卫星定位精度,验证了其在光学智能遥感卫星中的可行性。