PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Journal of the Korean Society of Hazard Mitigation10.9798/kosham.2021.21.3.1932021213193-201Flood Stage Forecasting at the Gurye-Gyo Station in Sumjin River Using LSTM-Based Deep Learning ModelsJaewon Jung, Hyelim Mo, Junhyeong Lee, Younghoon Yoo, Hung Soo Kimhttp://j-kosham.or.kr/upload/pdf/KOSHAM-2021-21-3-193.pdf, http://j-kosham.or.kr/journal/view.php?doi=10.9798/KOSHAM.2021.21.3.193, http://j-kosham.or.kr/upload/pdf/KOSHAM-2021-21-3-193.pdf
2021 Moratuwa Engineering Research Conference (MERCon)10.1109/mercon52712.2021.95256702021Short-Term Traffic Forecasting using LSTM-based Deep Learning ModelsDilantha Haputhanthri, Adeesha Wijayasirihttp://xplorestaging.ieee.org/ielx7/9525629/9525634/09525670.pdf?arnumber=9525670
10.36227/techrxiv.151036022021Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning ModelsJaydip Sen, Sidra Mehtab, Abhishek Duttahttps://ndownloader.figshare.com/files/29037078
10.36227/techrxiv.15103602.v12021Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning ModelsJaydip Sen, Sidra Mehtab, Abhishek Duttahttps://ndownloader.figshare.com/files/29037078
10.21203/rs.3.rs-1233741/v12022An approach for forecasting the Onion Price volatility in Indian Wholesale Markets using hybrid GARCH-LSTM Deep learning modelsShivam Swarup, Gyaneshwar Singh Kushwahahttps://www.researchsquare.com/article/rs-1233741/v1, https://www.researchsquare.com/article/rs-1233741/v1.html
Water10.3390/w13121612202113121612Flood Stage Forecasting Using Machine-Learning Methods: A Case Study on the Parma River (Italy)Susanna Dazzi, Renato Vacondio, Paolo Mignosahttps://www.mdpi.com/2073-4441/13/12/1612/pdf
10.21203/rs.3.rs-740568/v12021Deep Learning Based Models: Basic LSTM, Bi LSTM, Stacked LSTM, CNN LSTM and Conv LSTM to Forecast Agricultural Commodities PricesR. Murugesan, Eva Mishra, Akash Hari Krishnanhttps://www.researchsquare.com/article/rs-740568/v1, https://www.researchsquare.com/article/rs-740568/v1.html
Advances in Distributed Computing and Machine Learning10.1007/978-981-16-4807-6_392022405-423Analysis and Forecasting of Financial Time Series Using CNN and LSTM-Based Deep Learning ModelsSidra Mehtab, Jaydip Senhttps://link.springer.com/content/pdf/10.1007/978-981-16-4807-6_39
Environmental Science and Pollution Research10.1007/s11356-021-13875-w202129912875-12889Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validationSakshi Khullar, Nanhey Singhhttps://link.springer.com/content/pdf/10.1007/s11356-021-13875-w.pdf, https://link.springer.com/article/10.1007/s11356-021-13875-w/fulltext.html, https://link.springer.com/content/pdf/10.1007/s11356-021-13875-w.pdf
International Journal of Agricultural and Environmental Information Systems10.4018/ijaeis.2020070102202011313-30A Novel Approach for Wind Speed Forecasting Using LSTM-ARIMA Deep Learning ModelsVikram Bali, Ajay Kumar, Satyam Gangwarhttps://www.igi-global.com/viewtitle.aspx?TitleId=256988