Results 21 to 30 of about 825,885 (311)
Sequential data assimilation for real-time probabilistic flood inundation mapping [PDF]
Hydrology and Earth System Sciences, 2021 Real-time probabilistic flood inundation mapping is crucial for flood risk warning and decision-making during the emergency period before an upcoming flood event.
K. Jafarzadegan +2 more
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BundleNet: Learning with Noisy Label via Sample Correlations
IEEE Access, 2018 Sequential patterns are important, because they can be exploited to improve the prediction accuracy of our classifiers. Sequential data, such as time series/video frames, and event data are becoming more and more ubiquitous in a wide spectrum of ...
Chenghua Li +5 more
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J48SS: A Novel Decision Tree Approach for the Handling of Sequential and Time Series Data
Computers, 2019 Temporal information plays a very important role in many analysis tasks, and can be encoded in at least two different ways. It can be modeled by discrete sequences of events as, for example, in the business intelligence domain, with the aim of tracking ...
Andrea Brunello +3 more
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Sequential Ambiguity Resolution Method for Poorly-Observed GNSS Data
Remote Sensing, 2021 Integer ambiguity resolution is required to obtain precise coordinates for the global navigation satellite system (GNSS). Poorly observed data cause unfixed integer ambiguity and reduce the coordinate accuracy.
Haiyang Li +3 more
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Sequential Hierarchical Pattern Clustering [PDF]
, 2009 Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all pairwise distances between patterns must be computed in advance.
Niranjan, Mahesan +5 more
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Parallel graph-based anomaly detection technique for sequential data
Journal of King Saud University: Computer and Information Sciences, 2022 In data mining, outlier detection is applied in different domains. It has very large applications such as energy consumption analysis, forecasting hurricanes in meteorological data, fraud and intrusion detection, event detection and system monitoring in ...
Ahmed Farag +2 more
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Segmentation of Subspaces in Sequential Data
CoRR, 2015 We propose Ordered Subspace Clustering (OSC) to segment data drawn from a sequentially ordered union of subspaces. Similar to Sparse Subspace Clustering (SSC) we formulate the problem as one of finding a sparse representation but include an additional penalty term to take care of sequential data.
Stephen Tierney, Yi Guo 0001, Junbin Gao
openaire +2 more sources
StreamingBandit: Experimenting with Bandit Policies
Journal of Statistical Software, 2020 A large number of statistical decision problems in the social sciences and beyond can be framed as a (contextual) multi-armed bandit problem. However, it is notoriously hard to develop and evaluate policies that tackle these types of problems, and to use
Jules Kruijswijk +3 more
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Parallel Sequential Pattern Mining of Massive Trajectory Data [PDF]
International Journal of Computational Intelligence Systems, 2010 The trajectory pattern mining problem has recently attracted much attention due to the rapid development of location-acquisition technologies, and parallel computing essentially provides an alternative method for handling this problem.
Shaojie Qiao, Tianrui Li, Jing Peng
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PrefixSpan Based Pattern Mining Using Time Sliding Weight From Streaming Data
IEEE Access, 2020 This study proposes the prefixSpan based pattern mining using time sliding weight from streaming data. To discover sequential patterns, it applies a time sliding weight to create a structure of projected DB Tree.
Ji-Soo Kang +2 more
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