Novel residual hybrid machine learning for solar activity prediction in smart cities

RA Abdulkadir, MK Hasan, S Islam… - Earth Science …, 2023 - Springer
Predicting global solar activity is crucial for smart cities, especially for space activities,
communication industries, and climate change monitoring. The recently developed models …

Applying Bayesian inference in a hybrid CNN-LSTM model for time-series prediction

TL Nghiem, VD Le, TL Le, P Maréchal… - … Analysis and Pattern …, 2022 - ieeexplore.ieee.org
Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) provide state-
of-the-art performance in various tasks. However, these models are faced with overfitting on …

A Machine Learning Approach for Earthquake Prediction in Various Zones Based on Solar Activity

V Shkurastky, AB Usman, M O'Dea… - … of Computer and …, 2024 - sure.sunderland.ac.uk
—This paper examines relationships between solar activity and earthquakes, it applied
machine learning techniques: Knearest neighbour, support vector regression, random forest …

[HTML][HTML] Predicting sunspot number from topological features in spectral images I: Machine learning approach

D Sierra-Porta, M Tarazona-Alvarado… - Astronomy and …, 2024 - Elsevier
This study presents an advanced machine learning approach to predict the number of
sunspots using a comprehensive dataset derived from solar images provided by the Solar …

Ensembles of Rnns Negatively Correlated Through Time Using Bptt and Rtrl

A Rodan, O Al-Kadi, AK Al-Tamimi, Y Javed - Available at SSRN 4706199 - papers.ssrn.com
Abstract Recurrent Neural Network (RNN) can offer more expressive power to approximate
nonlinear dynamical systems compared to Feedforward Neural Network (FFNN). Their …

A Review of Machine Learning Methods Applied in Sunspot Prediction

Z Xiao - 2021 International Conference on Networking …, 2021 - ieeexplore.ieee.org
Solar activity has a significant impact on the production and life of human beings and
organisms on earth. Since solar activity varies in a cycle of approximately 11 years, the …