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Artificial intelligence in physical sciences: Symbolic regression trends and perspectives
Symbolic regression (SR) is a machine learning-based regression method based on genetic
programming principles that integrates techniques and processes from heterogeneous …
programming principles that integrates techniques and processes from heterogeneous …
Machine learning and deep learning in energy systems: A review
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 …
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
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 …
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
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 …
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 …
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
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 …
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
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 …
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 …
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 …
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
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 …
at a rate of 85%. This dominant use of fossil-based fuels has led to an accelerating increase …