Mining temporal association rules with frequent itemsets tree
L Wang, J Meng, P Xu, K Peng - Applied Soft Computing, 2018 - Elsevier
A novel framework for mining temporal association rules by discovering itemsets with
frequent itemsets tree is introduced. In order to solve the problem of handling time series by …
frequent itemsets tree is introduced. In order to solve the problem of handling time series by …
Development of adaptive time-weighted dynamic time warping for time series vegetation classification using satellite images in Solapur district
M Kumawat, A Khaparde - The Computer Journal, 2023 - academic.oup.com
The global seasonal change and continued rapid growth have maximized the need to
assess the urban dwellers' depend on vegetation for their lives, and also in the urban …
assess the urban dwellers' depend on vegetation for their lives, and also in the urban …
Object-oriented satellite image time series analysis using a graph-based representation
L Khiali, D Ienco, M Teisseire - Ecological informatics, 2018 - Elsevier
Nowadays, remote sensing technologies produce huge amounts of satellite images that can
be helpful to monitor geographical areas over time. A satellite image time series (SITS) …
be helpful to monitor geographical areas over time. A satellite image time series (SITS) …
Histogram-based spatio-temporal feature classification of vegetation indices time-series for crop mapping
Classification of time-series of vegetation indices (VIs) can be a reliable strategy for
identifying and monitoring different crop types. Recently, with the advent of new sensors, the …
identifying and monitoring different crop types. Recently, with the advent of new sensors, the …
NORCAMA: Change analysis in SAR time series by likelihood ratio change matrix clustering
This paper presents a likelihood ratio test based method of change detection and
classification for synthetic aperture radar (SAR) time series, namely NORmalized Cut on …
classification for synthetic aperture radar (SAR) time series, namely NORmalized Cut on …
An efficient pixel clustering-based method for mining spatial sequential patterns from serial remote sensing images
X Wu, X Zhang - Computers & Geosciences, 2019 - Elsevier
The accumulation of serial remote sensing images provides plentiful data for discovering
sequential spatial patterns in various fields such as agricultural monitoring, urban …
sequential spatial patterns in various fields such as agricultural monitoring, urban …
Data mining, a promising tool for large-area cropland mapping
The northern fringe of sub-Saharan Africa is a region that is considered to be particularly
vulnerable to climate variability and change, and it is a location in which food security …
vulnerable to climate variability and change, and it is a location in which food security …
[HTML][HTML] Discovery of temporal association rules with hierarchical granular framework
TP Hong, GC Lan, JH Su, PS Wu, SL Wang - Applied Computing and …, 2016 - Elsevier
Most of the existing studies in temporal data mining consider only lifespan of items to find
general temporal association rules. However, an infrequent item for the entire time may be …
general temporal association rules. However, an infrequent item for the entire time may be …
Swap randomization of bases of sequences for mining satellite image times series
Swap randomization has been shown to be an effective technique for assessing the
significance of data mining results such as Boolean matrices, frequent itemsets, correlations …
significance of data mining results such as Boolean matrices, frequent itemsets, correlations …