ITM Web Conf.
Volume 47, 20222022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|Number of page(s)||6|
|Section||Algorithm Optimization and Application|
|Published online||23 June 2022|
- HOCHREITER, SCHMIDHUBER. Long short-term memory [J].Neural computation, 1997, 9(8):1735-80. [CrossRef] [Google Scholar]
- ELSAID A, JAMIY F E, HIGGINS J, et al. Optimizing long short-term memory recurrent neural networks using ant colony optimization to predict turbine engine vibration [J].Applied Soft Computing, 2018, 73:969 - 91. [CrossRef] [Google Scholar]
- ABBASVANDI Z, NASRABADI A M.A self-organized recurrent neural network for estimating the effective connectivity and its application to EEG data [J].Computers in Biology and Medicine, 2019, 110:93 - 107. [CrossRef] [Google Scholar]
- CHUNG J, GULCEHRE C, CHO K, et al. Empirical evaluation of gated recurrent neural networks on sequence modeling [EB]. arXiv:14123555,2014. [Google Scholar]
- ZHOU G-B, WU J, ZHANG C-L, et al. Minimal gated unit for recurrent neural networks [J].International Journal of Automation, 2016, 13(3):226-34. [CrossRef] [Google Scholar]
- COLLINS J, SOHL-DICKSTEIN J, SUSSILLO D. Capacity and trainability in recurrent neural networks [EB]. arXiv:161109913,2016. [Google Scholar]
- ORORBIA A, ELSAID A, DESELL T. Investigating recurrent neural network memory structures using neuro-evolution [C]//Proceedings of the Genetic and Evolutionary Computation Conference. ACM,2019:446-55. [Google Scholar]
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