%0 Journal Article %1 Tavakoli_2020 %A Tavakoli, Neda %A Siami-Namini, Sima %A Khanghah, Mahdi Adl %A Soltani, Fahimeh Mirza %A Namin, Akbar Siami %D 2020 %I Springer Science and Business Media LLC %J SN Applied Sciences %K autoencoder timeseries %N 5 %R 10.1007/s42452-020-2584-8 %T An autoencoder-based deep learning approach for clustering time series data %U https://doi.org/10.1007%2Fs42452-020-2584-8 %V 2

@article{Tavakoli_2020, added-at = {2022-02-11T14:35:55.000+0100}, author = {Tavakoli, Neda and Siami-Namini, Sima and Khanghah, Mahdi Adl and Soltani, Fahimeh Mirza and Namin, Akbar Siami}, biburl = {https://www.bibsonomy.org/bibtex/2e8aa44c0d203c4c5d0699b4538b9eb71/albinzehe}, doi = {10.1007/s42452-020-2584-8}, interhash = {e958f2e634dea63207f297f489ca3e60}, intrahash = {e8aa44c0d203c4c5d0699b4538b9eb71}, journal = {{SN} Applied Sciences}, keywords = {autoencoder timeseries}, month = apr, number = 5, publisher = {Springer Science and Business Media {LLC}}, timestamp = {2022-02-11T14:35:55.000+0100}, title = {An autoencoder-based deep learning approach for clustering time series data}, url = {https://doi.org/10.1007%2Fs42452-020-2584-8}, volume = 2, year = 2020 }