Eight years of AutoML: categorisation, review and trends
Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …
applied in a large number of application domains. However, apart from the required …
A review of designs and applications of echo state networks
Recurrent Neural Networks (RNNs) have demonstrated their outstanding ability in sequence
tasks and have achieved state-of-the-art in wide range of applications, such as industrial …
tasks and have achieved state-of-the-art in wide range of applications, such as industrial …
A systematic review of echo state networks from design to application
A recurrent neural network (RNN) has demonstrated its outstanding ability in sequence
tasks and has achieved state of the art in many applications, such as industrial and medical …
tasks and has achieved state of the art in many applications, such as industrial and medical …
A hybrid sparrow search algorithm of the hyperparameter optimization in deep learning
Deep learning has been widely used in different fields such as computer vision and speech
processing. The performance of deep learning algorithms is greatly affected by their …
processing. The performance of deep learning algorithms is greatly affected by their …
On the post-hoc explainability of deep echo state networks for time series forecasting, image and video classification
Since their inception, learning techniques under the reservoir computing paradigm have
shown a great modeling capability for recurrent systems without the computing overheads …
shown a great modeling capability for recurrent systems without the computing overheads …
Short-term memory capacity analysis of Lu3Fe4Co0.5Si0.5O12-based spin cluster glass towards reservoir computing
Reservoir computing is a brain heuristic computing paradigm that can complete training at a
high speed. The learning performance of a reservoir computing system relies on its …
high speed. The learning performance of a reservoir computing system relies on its …
Error-driven chained multiple-subnetwork echo state network for time-series prediction
J Huang, Y Li, YAW Shardt, L Qiao, M Shi… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Hybrid echo state networks (ESNs), a type of modified ESN, have been developed to
improve the prediction accuracy of ESNs. However, they have been criticized for their …
improve the prediction accuracy of ESNs. However, they have been criticized for their …
[引用][C] Comparison of optimization techniques based on gradient descent algorithm: A review
SH Haji, AM Abdulazeez - PalArch's Journal of Archaeology of Egypt/Egyptology, 2021
Optimized echo state Network based on PSO and Gradient Descent for choatic time series prediction
R Soltani, E Benmohamed, H Ltifi - 2022 IEEE 34th …, 2022 - ieeexplore.ieee.org
Echo State Network (ESN), as a paradigm of Reservoir Computing (RC), refers to a well-
known Recurrent Neural Network (RNN). Its randomly generated reservoir represents the …
known Recurrent Neural Network (RNN). Its randomly generated reservoir represents the …
[HTML][HTML] Математическая модель формирования ценовой политики и плана производственнотранспортной системы лесопромышленного предприятия
РС Рогулин - Бизнес-информатика, 2021 - cyberleninka.ru
Формирование цепей поставок сырья тесно связано с проблемами производства,
касающимися определения цен на реализуемые товары. Часто возникает вопрос о …
касающимися определения цен на реализуемые товары. Часто возникает вопрос о …