Metaheuristic algorithms for solar radiation prediction: A systematic analysis

SA Pérez-Rodríguez, JM Álvarez-Alvarado… - IEEE …, 2024 - ieeexplore.ieee.org
In the contemporary world, where the escalating demand for energy and the imperative for
sustainable sources, notably solar energy, have taken precedence, the investigation into …

[HTML][HTML] Predicting Tilapia Productivity in Geothermal Ponds: A Genetic Algorithm Approach for Sustainable Aquaculture Practices

V Tynchenko, O Kukartseva, Y Tynchenko, V Kukartsev… - Sustainability, 2024 - mdpi.com
This study presents a case focused on sustainable farming practices, specifically the
cultivation of tilapia (Mozambican and aureus species) in ponds with geothermal water. This …

Integrated machine learning for modeling bearing capacity of shallow foundations

Y Liu, Y Liang - Scientific Reports, 2024 - nature.com
Analyzing the stability of footings is a significant step in civil/geotechnical engineering
projects. In this work, two novel predictive tools are suggested based on an artificial neural …

Neuromorphic Computing-Based Model for Short-Term Forecasting of Global Horizontal Irradiance In Saudi Arabia

A Alharbi, U Ahmed, T Alharbi, A Mahmood - IEEE Access, 2024 - ieeexplore.ieee.org
To tackle environmental and increasing energy demand issues, different energy transition
options have been investigated. Solar power has vast resources and is environment …

Satin Bowerbird optimizer-neural network for approximating the capacity of CFST columns under compression

Y Liu, Y Liang - Scientific Reports, 2024 - nature.com
Concrete-filled steel tube columns (CFSTCs) are important elements in the construction
sector and predictive analysis of their behavior is essential. Recent works have revealed the …

Towards Automated Model Selection for Wind Speed and Solar Irradiance Forecasting

K Blazakis, N Schetakis, P Bonfini… - Sensors (Basel …, 2024 - pmc.ncbi.nlm.nih.gov
Given the recent increase in demand for electricity, it is necessary for renewable energy
sources (RESs) to be widely integrated into power networks, with the two most commonly …

Machine learning-driven solar irradiance prediction: advancing renewable energy in Rajasthan

A Tandon, A Awasthi, KC Pattnayak, A Tandon… - Discover Applied …, 2025 - Springer
This research explores the potential of solar power as an eco-friendly alternative to fossil
fuels, focusing on Rajasthan, India. Using data from MERRA-2, researchers analysed solar …

Desenvolvimento de algoritmo para geração de séries sintéticas de radiação solar e temperatura para cidades brasileiras

M Lago - 2024 - lume.ufrgs.br
A substituição gradual das fontes de energia oriundas de combustíveis fósseis por fontes de
energia renováveis e não poluentes é cada vez mais necessária, apesar do ainda …

Enhancing solar PV power production prediction: assessing input data for improved accuracy

H Ahmadnejad - 2022 - politesi.polimi.it
Accurate forecasting of solar photovoltaic (PV) power generation is vital for effective energy
management and grid stability, particularly as renewable energy sources become more …