[HTML][HTML] A review of the use of artificial neural network models for energy and reliability prediction. A study of the solar PV, hydraulic and wind energy sources

J Ferrero Bermejo, JF Gómez Fernández… - Applied Sciences, 2019 - mdpi.com
The generation of energy from renewable sources is subjected to very dynamic changes in
environmental parameters and asset operating conditions. This is a very relevant issue to be …

A taxonomical review on recent artificial intelligence applications to PV integration into power grids

C Feng, Y Liu, J Zhang - International Journal of Electrical Power & Energy …, 2021 - Elsevier
The exponential growth of solar power has been witnessed in the past decade and is
projected by the ambitious policy targets. Nevertheless, the proliferation of solar energy …

[HTML][HTML] Photovoltaic power forecast using deep learning techniques with hyperparameters based on bayesian optimization: A case study in the galapagos islands

R Guanoluisa, D Arcos-Aviles, M Flores-Calero… - Sustainability, 2023 - mdpi.com
Hydropower systems are the basis of electricity power generation in Ecuador. However,
some isolated areas in the Amazon and Galapagos Islands are not connected to the …

Correlation analysis between higher education level and college students' public mental health driven by AI

Y Cai, L Tang - Computational intelligence and neuroscience, 2022 - Wiley Online Library
Generally, there is a certain correlation between the level of higher education and the public
mental health of college students. Traditionally, questionnaires and literature research …

Solar energy production forecasting through artificial neuronal networks, considering the Föhn, north and south winds in San Juan, Argentina

LC Parra Raffán, A Romero… - The Journal of …, 2019 - Wiley Online Library
This study presents a method to predict a day‐ahead solar irradiation curve, under extreme
meteorological phenomena (Föhn, north and south winds), existing in the province of San …

Short-Term forecasting of photovoltaic power in an isolated area of Ecuador using deep learning techniques

R Guanoluisa-Pineda, A Ibarra… - 2022 11th …, 2022 - ieeexplore.ieee.org
In Ecuador, electricity generation is mainly covered by renewable energy sources that feed
the National Interconnected System (NIS). Its economical price means that the installation of …

[HTML][HTML] Energy prediction using evolutionary lean neural networks

YW Foo - 2022 - theses.gla.ac.uk
The demand for data center services, driven by the surge in online applications and
services, has propelled energy consumption to unprecedented levels. While renewable …

Application of Recurrent Neural Network Model in the Analysis of Electricity Load Demand in Ashanti Region of Ghana

FK Oduro-Gyimah - 2018 IEEE 7th International Conference on …, 2018 - ieeexplore.ieee.org
In order to supply electric energy to the customer in a secure and economic manner, an
electric company faces many economical and technical challenges in operation. These …

Solar irradiation forecasting through a hybrid method, considering zonda, north and south winds in San Juan, Argentina

LCP Raffán, A Romero… - 2018 IEEE Biennial …, 2018 - ieeexplore.ieee.org
This paper presents a hybrid method to predict a day-ahead solar irradiation curve, under
extreme meteorological phenomena (Zonda, North, South winds), existing in the province of …

Redes neurais artificiais aplicadas à previsão de irradiância global horizontal no contexto de cidades energeticamente inteligentes

F Pedro Bon - 2020 - repositorio.ufscar.br
O Brasil, um país de dimensão continental, abarca mais de 8 milhões de quilômetros
quadrados, conforme a Resolução nº 02, de 29/06/2017 do Diário Oficial da União nº 124 …