Suchergebnisse - "Backpropagation through time algorithms"

Training Bidirectional Recurrent Neural Network Architectures with the Scaled Conjugate Gradient Algorithm

Autoren: Agathocleous, Michalis Christodoulou, Chris C. Promponas, Vasilis J. et al.

Weitere Verfasser: Agathocleous, Michalis Christodoulou, Chris C. Promponas, Vasilis J. et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783319447773
25th International Conference on Artificial Neural Networks, ICANN 2016
Lect. Notes Comput. Sci.

Schlagwörter: 0301 basic medicine, Artificial intelligence, Ensemble methods, Bioinformatics, Backpropagation through time algorithms, Learning algorithms, Conjugate gradient method, Topology, 7. Clean energy, Filtering technique, 03 medical and health sciences, Scaled conjugate gradient algorithm, Trans-membrane proteins, Computational intelligence, Scaled conjugate gradient, 0303 health sciences, Backpropagation algorithms, Learning systems, Network architecture, Bidirectional recurrent neural networks, Proteins, Protein secondary structure prediction, Transmembrane protein topology prediction, Recurrent neural networks, Scaled conjugate gradients, Protein secondary-structure prediction, Neural networks, Forecasting

Zugangs-URL: https://link.springer.com/chapter/10.1007/978-3-319-44778-0_15/fulltext.html
https://dblp.uni-trier.de/db/conf/icann/icann2016-1.html#AgathocleousCPK16
https://rd.springer.com/chapter/10.1007%2F978-3-319-44778-0_15
https://link.springer.com/chapter/10.1007/978-3-319-44778-0_15
http://gnosis.library.ucy.ac.cy/handle/7/53500

Active Stabilization of Line-Regulating Converters with Constant Power Loads

Autoren: Mueller, Jacob A. Wunsch, Donald C. Kimball, Jonathan W.

Quelle: Electrical and Computer Engineering Faculty Research & Creative Works

Schlagwörter: Backpropagation Algorithms, Dynamic Programming, Numerical Methods, Power Converters, Runge Kutta Methods, Back-Propagation Through Time, Backpropagation Through Time Algorithms, Controller Performance, Distribution Systems, Micro Grid, Non-Ideal Conditions, Numerical Integrations, Value-Gradient Learning, Backpropagation, DC Microgrids, Electrical and Computer Engineering

Relation: https://scholarsmine.mst.edu/ele_comeng_facwork/2930; https://doi.org/10.1109/NAPS.2017.8107237

Verfügbarkeit: https://scholarsmine.mst.edu/ele_comeng_facwork/2930
https://doi.org/10.1109/NAPS.2017.8107237