... Deep learning for time series forecasting : Tutorial and literature survey . ACM Computing Surveys , 55 ( 6 ) , 1-36 . ISSN 0360-0300 . https://doi.org/10.1145/3533382 Bica , I. , Alaa , A. M. , Jordon , J. , & van der Schaar , M ...
... ., et al.: Data augmentation techniques in time series domain: A survey and taxonomy. arXiv preprint arXiv:220613508 (2022) updates 2 5 1 4 Prediction of Deposition Parameters in Optimizing Biomass Forecasting and Supply Chain 71 ...
Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality.
... machine learning models . J. Hydrol . 587 , 124989 ( 2020 ) 3. Benidis , K. , et al .: Deep learning for time series forecasting : tutorial and literature survey . ACM Comput . Surv . 55 ( 6 ) , 1-36 ( 2022 ) 4. Bi , J. , Zhang , L ...
... review and tutorial article, “Deep Learning for Time Series Forecasting: Tutorial and Literature Survey”, Benidis et al., ACM Computing Surveys 55(6), 2023, article No.: 12, can be found at https://dl.acm.org/doi/10.1145/3533382. The ...
... literature review shows that ML methods play crucial roles in the domain of forecasting time series data. The use of ... Tutorial Survey of Architectures, Algorithms, and Application for Deep Learning-ERRATUM”. APSIPA Transaction ...
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics.
... time series data mining. Eng Appl Artif Intell. (2011) 24:164–81. doi: 10.1016/j.engappai.2010.09.007 2. Bello-Orgaz ... literature review and challenges. Int J Distribut Sensor Netw. (2015) 11:431047. doi: 10.1155/2015/431047 4 ...
This book contains selected papers from the 7th International Conference on Information Science and Applications (ICISA 2016) and provides a snapshot of the latest issues encountered in technical convergence and convergences of security ...