Artificial intelligence in physical sciences: Symbolic regression trends and perspectives

D Angelis, F Sofos, TE Karakasidis - Archives of Computational Methods …, 2023 - Springer
Symbolic regression (SR) is a machine learning-based regression method based on genetic
programming principles that integrates techniques and processes from heterogeneous …

Machine learning and deep learning in energy systems: A review

MM Forootan, I Larki, R Zahedi, A Ahmadi - Sustainability, 2022 - mdpi.com
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …

Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system

P Sharma, Z Said, A Kumar, S Nizetic, A Pandey… - Energy & …, 2022 - ACS Publications
Nanofluids have gained significant popularity in the field of sustainable and renewable
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …

How solar radiation forecasting impacts the utilization of solar energy: A critical review

N Krishnan, KR Kumar, CS Inda - Journal of Cleaner Production, 2023 - Elsevier
The demand for energy generation from solar energy resource has been exponentially
increasing in recent years. It is integral for a grid operator to maintain the balance between …

Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms

Ü Ağbulut - Sustainable Production and Consumption, 2022 - Elsevier
Adverse impacts of the transportation sector on not only air quality but also economic growth
of a country are nowadays well-noticed, particularly by develo** countries. Today, the …

Machine learning-based time series models for effective CO2 emission prediction in India

S Kumari, SK Singh - Environmental Science and Pollution Research, 2023 - Springer
China, India, and the USA are the countries with the highest energy consumption and CO 2
emissions globally. As per the report of datacommons. org, CO 2 emission in India is 1.80 …

Potential of explainable artificial intelligence in advancing renewable energy: challenges and prospects

VN Nguyen, W Tarełko, P Sharma, AS El-Shafay… - Energy & …, 2024 - ACS Publications
Modern machine learning (ML) techniques are making inroads in every aspect of renewable
energy for optimization and model prediction. The effective utilization of ML techniques for …

A review on global solar radiation prediction with machine learning models in a comprehensive perspective

Y Zhou, Y Liu, D Wang, X Liu, Y Wang - Energy Conversion and …, 2021 - Elsevier
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …

Multi-scale solar radiation and photovoltaic power forecasting with machine learning algorithms in urban environment: A state-of-the-art review

J Tian, R Ooka, D Lee - Journal of Cleaner Production, 2023 - Elsevier
Solar energy has been rapidly utilized in urban environments owing to its significant
potential to fulfill the energy demand. The precise forecasting of solar energy, including solar …

Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms

MS Bakay, Ü Ağbulut - Journal of Cleaner Production, 2021 - Elsevier
Today, the world's primary energy demand has been met by the burning of fossil-based fuels
at a rate of 85%. This dominant use of fossil-based fuels has led to an accelerating increase …