Temat: Adaptive learning - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Adaptive controller design for electric drive with variable parameters by Reinforcement Learning method
Autorzy:: Pajchrowski, T.
Siwek, P.
Wójcik, A.
Powiązania:: https://bibliotekanauki.pl/articles/201068.pdf
Data publikacji:: 2020
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: Reinforcement Learning
adaptive control
electric drive
machine learning
Opis:: The paper presents a method for designing a neural speed controller with use of Reinforcement Learning method. The controlled object is an electric drive with a synchronous motor with permanent magnets, having a complex mechanical structure and changeable parameters. Several research cases of the control system with a neural controller are presented, focusing on the change of object parameters. Also, the influence of the system critic behaviour is researched, where the critic is a function of control error and energy cost. It ensures long term performance stability without the need of switching off the adaptation algorithm. Numerous simulation tests were carried out and confirmed on a real stand.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 5; 1019-1030
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Probabilistic adaptive computation time
Autorzy:: Figurnov, M.
Sobolev, A.
Vetrov, D.
Powiązania:: https://bibliotekanauki.pl/articles/201248.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: deep learning
probabilistic models
adaptive computation time
uczenie głębokie
modele probabilistyczne
adaptacyjny czas obliczeniowy
Opis:: We present a probabilistic model with discrete latent variables that control the computation time in deep learning models such as ResNets and LSTMs. A prior on the latent variables expresses the preference for faster computation. The amount of computation for an input is determined via amortized maximum a posteriori (MAP) inference. MAP inference is performed using a novel stochastic variational optimization method. The recently proposed adaptive computation time mechanism can be seen as an ad-hoc relaxation of this model. We demonstrate training using the general-purpose concrete relaxation of discrete variables. Evaluation on ResNet shows that our method matches the speed-accuracy trade-off of adaptive computation time, while allowing for evaluation with a simple deterministic procedure that has a lower memory footprint.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 6; 811-820
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Coherent structures and flow control: genesis and prospect
Autorzy:: Gad-El-Hak, M.
Powiązania:: https://bibliotekanauki.pl/articles/201471.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: smart wings
coherent structures
reactive flow control
adaptive control
machine-learning control
futuristic control systems
microsensors
microactuators
artificial intelligence
turbulent shear flows
history of flow control
history of coherent structures
inteligentne skrzydła
kontrola adaptacyjna
mikroczujniki
sztuczna inteligencja
Opis:: The genesis of both coherent structures and reactive flow control strategies is explored. Futuristic control systems that utilize microsensors and microactuators together with artificial intelligence to target specific coherent structures in a transitional or turbulent flow are considered. Of possible interest to the readers of this journal is the concept of smart wings, to be briefly discussed early in the article.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 3; 411-444
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

Artykuł

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