Divide and conquer: Learning chaotic dynamical systems with multistep penalty neural ordinary differential equations

D Chakraborty, SW Chung, T Arcomano… - Computer Methods in …, 2024 - Elsevier
Forecasting high-dimensional dynamical systems is a fundamental challenge in various
fields, such as geosciences and engineering. Neural Ordinary Differential Equations …

Optimization of Echo State Neural Networks to Solve Classification Problems

AC Ramírez, LGD Fraga - Study of Complex Systems and their …, 2023 - Springer
Abstract Echo State Neural Networks (ESNN) are a kind of recurrent neural networks, which
are computationally very cheap to train: input and reservoir weights are initialized randomly …

Machine Learning Based Approaches to Dynamic Wind Estimation for Unmanned Aerial Vehicles

A Baraka - 2023 - search.proquest.com
Wind estimation techniques for Unmanned Aerial Vehicles (UAVs) using data-oriented
machine learning (ML) algorithms are studied in this thesis. These ML-based methods work …

Machine learning techniques to mitigate nonlinear impairments in optical fiber system

PJ Freire de Carvalho Souza - 2022 - publications.aston.ac.uk
The upcoming deployment of 5/6G networks, online services like 4k/8k HDTV (streamers
and online games), the development of the Internet of Things concept, connecting billions of …

[PDF][PDF] Reservoir Computing in Alpha Forecasting of Foreign Exchange Market

Y He - imperial.ac.uk
Deep learning algorithms have long been implemented in financial industry for pricing,
return prediction and so on. However, some complicated models may lead to expensive …

Aplicações de reservoir computing e sistemas não-lineares para forecasting

KGR Pergher - 2022 - lume.ufrgs.br
Em meio a um cenário de forte competição impulsionado por tecnologias disruptivas, novos
paradigmas técnicos e operacionais e o advento de aplicações em ciência de dados e …