[HTML][HTML] Echo state networks: novel reservoir selection and hyperparameter optimization model for time series forecasting

CH Valencia, MMBR Vellasco, K Figueiredo - Neurocomputing, 2023 - Elsevier
The use of computational intelligence models for multi-step time series forecasting tasks has
presented satisfactory results in such a way that they are considered models with an …

Machine learning controller for data rate management in science DMZ networks

C Vega, EF Kfoury, J Gomez, JE Pezoa, M Figueroa… - Computer Networks, 2024 - Elsevier
This article presents a Machine Learning Controller (MLC) supported by a P4 switch for
improving rate control in non-dedicated Science Demilitarized Zone (Science DMZ) …

Design of a Type Two Fuzzy-based system to Control the Pitch Rate of the Cessna Citation X

S Hosseini, G Ghazi, RM Botez - AIAA AVIATION 2023 Forum, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-3802. vid In this research, a novel
control methodology developed at the Laboratory of Applied Research in Active Controls …

Design and implementation of a machine-learning observer for sensorless PMSM drive control

DS Putra, SC Chen, HH Khong, F Cheng - Applied Sciences, 2022 - mdpi.com
Information about rotor positions is critical when controlling a permanent-magnet
synchronous motor (PMSM). This information can be gathered using a sensor or through an …

Analytical design of optimal fractional order pid control for industrial robot based on digital twin

X Liu, Y Luo - 2022 IEEE 2nd International Conference on …, 2022 - ieeexplore.ieee.org
This paper proposes a fractional order PID analytical design framework for industrial robot
based on digital twin. The effectiveness of the digital twin real-time optimization framework is …

Model-referenced Adaptive Flight Controller based on Recurrent Neural Network for the Longitudinal Motion of Cessna Citation X

S Hosseini, C Inga, G Ghazi, RM Botez - AIAA AVIATION 2023 Forum, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-3797. vid This paper presents a
methodology developed at the Laboratory of Applied Research in Active Controls, Avionics …

TEC forecasting using optimized variational mode decomposition and elman neural networks

MM Shakir, Z Othman, AA Bakar - International Journal of …, 2022 - search.proquest.com
Forecasting the ionosphere layer's total electronic content (TEC) is crucial for its impact on
satellite signals and global positioning systems (GPS) and the ability to predict earthquakes …

Modelos de Predicción de Radiación Solar y Temperatura Ambiente mediante Redes Neuronales Recurrentes

A Cuesta, J Constante, D Jijón - Revista Técnica energía, 2023 - scielo.senescyt.gob.ec
RES El objetivo de este estudio es comparar dos arquitecturas de redes neuronales
recurrentes de Elman y Jordan (RNRE y RNRJ), enfocadas en predicción de dos días de …

Altitude and attitude control of a quadcopter based on neuro-fuzzy controller

D Korkmaz, H Acikgoz, M Ustundag - Proceedings of the 11th International …, 2022 - Springer
In this paper, a 6-degrees of freedom (DoF) nonlinear dynamic model of the quadcopter is
derived and a robust altitude and attitude control is proposed. The motion control is …

A Novel Adaptive Learning Systems for Type-2 Fuzzy Controller Based on Elman Neural Network

MT Nguyen, TL Le - 2024 7th International Conference on …, 2024 - ieeexplore.ieee.org
Although its advantages of handling input uncertainties and noises, Type-2 Fuzzy controller
faces the challenge of the trial-and-error process for evaluating so many control parameters …