Similar Pattern Locating in Time Series Data
A New Pattern Representation Method for Time-series Data
... of time-series and not being efficient for large ...IoT data analysis as one of the motivations of this ...proposed pattern representa- tion method, as the process is applied to the segments, ...
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Data-driven pattern identification and outlier detection in time series
... of data-driven pattern identification and outlier detection in time ...the time series as a matrix it becomes possible to use SVD to highlight the underlying patterns and ...a ...
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TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS
... temporal data mining is proposed. Using a pattern wavelet transform as a data mining tool has yielded meaningful ...the pattern wavelet and the underlying time ...such pattern ...
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Fast Pattern Matching In Stream Time Series Data for Electrical Applications
... In this paper, we have proposed a novel MSMI representation together with a multi step filtering scheme, which facilitates detecting both static and dynamic patterns over time-series stream efficiently. The ...
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Developing a pattern discovery method in time series data and its GPU acceleration
... Dynamic Time Warping (DTW) algorithm is widely used in finding the global alignment of time ...Many time series data mining and analytical problems can be solved by the DTW ...find ...
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Pattern-sensitive Time-series Anonymization and its Application to Energy-Consumption Data
... 2.1 The Smart Grid The smart grid is an initiative to save energy, based on consumption forecasts, the optimization of energy consumption, fine-grained resource planning and seam- less integration of decentralized ...
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Predefined pattern detection in large time series
... Predefined pattern Time series representation a b s t r a c t Predefined pattern detection from time series is an interesting and challenging ...of time series ...
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Pattern of government spending in Nigeria: a time series analysis
... the pattern of government spending in Nigeria using a time series analysis to compare the nature of government spending between the Pre-Democratic era (between 1984 to 1998) and Democratic era ...
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Online pattern recognition in subsequence time series clustering
... the time series TS (Line 4), then pass it to a module for analyzing subsequence ...frequent pattern maintenance algorithm in Line 6, which attempts to maintain an approximate history of all ...
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Time Series Data Visualization
... – Visualize multivariate long time series – Provide overview that can be zoomed in – Support interactive pattern search. – Support search by example patterns[r] ...
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MINING TIME SERIES DATA
... of data, most classic machine learning and data mining algorithms do not work well on time series data due to their unique structure; it is often the case that each individual ...
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Efficient LCSS Distance Measure for Searching of Similar Time Series Trajectories
... of similar moving objects trajectories due to its wide range of real time ...of similar trajectories of moving objects helps data mining users to take smart decisions and thereby improving the ...
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Discriminative Feature Extraction of Time-Series Data to Improve Temporal Pattern Detection using Classification Algorithms
... Research conducted using a Support Vector Machine and the traffic of malicious IPs showed the method effective at predicting cyber-attack incidences up to 3 months prior to their occurrence (Liu et al., 2015). A feature ...
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Detecting Rice Phenology in Paddy Fields with Complex Cropping Pattern Using Time Series MODIS Data
... MODIS data had to be classified into 12 classes, to represent 12 months of a ...monthly data into quarterly and yearly data has reduced the effect of the uncertainty in determining the limit of the ...
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Discovering Flood Recession Pattern in Hydrological Time Series Data Mining during the Post Monsoon Period
... recession pattern for the river discharge data in the river Brahmaputra ...of time series data mining techniques, the analysis has made for hydrological daily discharge time ...
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Discriminative Feature Extraction of Time-Series Data to Improve Temporal Pattern Detection using Classification Algorithms
... of data, how best to derive useful information from a given data set is not always ...temporal data stream containing millions of entries into a feature set which may be used to train a machine ...
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Clustering of Time-Series Data Streams
... Physiological Data Modeling Contest [31] was held at ICML 2004, as a workshop, and aimed at information extraction from streaming sensors ...training data set for the contest 1 consisted of approximately ...
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Anomaly Detection on Time Series Data
... The data set we used to test our heuristics is the electricity consumptions data released by ISSDA, Ireland on Electricity Consumption Survey using Smart Meters 1 ...The data set contains the ...
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On time series data and optimal parameters
... Solver is used to minimize MSE for the periods 1–20 by adjusting the smoothing constants , and within the limits 0 6 , , 6 1, as well as the initial parameter values for level, trend and seasons. This is implemented in ...
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Detection of Outliers in Time Series Data
... synthetic data sets with an average of 46 synthetic ...identified data set and synthetic data ...both data sets are similar ...two data vectors x1 and x2. In our case x1 = ...
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