Time-series clustering–a decade review
Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …
about classes. With emerging new concepts like cloud computing and big data and their vast …
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
In the last 5 years there have been a large number of new time series classification
algorithms proposed in the literature. These algorithms have been evaluated on subsets of …
algorithms proposed in the literature. These algorithms have been evaluated on subsets of …
k-shape: Efficient and accurate clustering of time series
The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …
substantial interest in the analysis and mining of time series. Clustering is one of the most …
Temporal multi-graph convolutional network for traffic flow prediction
M Lv, Z Hong, L Chen, T Chen… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Traffic flow prediction plays an important role in ITS (Intelligent Transportation System). This
task is challenging due to the complex spatial and temporal correlations (eg, the constraints …
task is challenging due to the complex spatial and temporal correlations (eg, the constraints …
A review on distance based time series classification
Time series classification is an increasing research topic due to the vast amount of time
series data that is being created over a wide variety of fields. The particularity of the data …
series data that is being created over a wide variety of fields. The particularity of the data …
China's commercial bank stock price prediction using a novel K-means-LSTM hybrid approach
Y Chen, J Wu, Z Wu - Expert Systems with Applications, 2022 - Elsevier
China's commercial Bank shares have become the backbone of the capital market. The
prediction of a bank's stock price has been a hot topic in the investment field. However, the …
prediction of a bank's stock price has been a hot topic in the investment field. However, the …
Distributed and parallel time series feature extraction for industrial big data applications
M Christ, AW Kempa-Liehr, M Feindt - ar**_distances_as_features_for_improved_time_series_classification/links/5c0ed52892851c39ebe437b5/Using-dynamic-time-war**-distances-as-features-for-improved-time-series-classification.pdf" data-clk="hl=en&sa=T&oi=gga&ct=gga&cd=9&d=13582693338160189283&ei=ihilZ_KxGJmp6rQPqKK8iA8" data-clk-atid="Y08aeqBrf7wJ" target="_blank">[PDF] researchgate.net
Using dynamic time war** distances as features for improved time series classification
RJ Kate - Data mining and knowledge discovery, 2016 - Springer
Dynamic time war** (DTW) has proven itself to be an exceptionally strong distance
measure for time series. DTW in combination with one-nearest neighbor, one of the simplest …
measure for time series. DTW in combination with one-nearest neighbor, one of the simplest …