[HTML][HTML] Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

SE Bibri, J Krogstie, A Kaboli, A Alahi - Environmental Science and …, 2024 - Elsevier
The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial
Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to …

Artificial neural networks based optimization techniques: A review

MGM Abdolrasol, SMS Hussain, TS Ustun, MR Sarker… - Electronics, 2021 - mdpi.com
In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …

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 …

A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids

S Aslam, H Herodotou, SM Mohsin, N Javaid… - … and Sustainable Energy …, 2021 - Elsevier
Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …

[HTML][HTML] Distributed energy systems: A review of classification, technologies, applications, and policies

TB Nadeem, M Siddiqui, M Khalid, M Asif - Energy Strategy Reviews, 2023 - Elsevier
The sustainable energy transition taking place in the 21st century requires a major
revam** of the energy sector. Improvements are required not only in terms of the …

[HTML][HTML] An overview of machine learning applications for smart buildings

K Alanne, S Sierla - Sustainable Cities and Society, 2022 - Elsevier
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …

[HTML][HTML] Unveiling the dynamics of AI applications: A review of reviews using scientometrics and BERTopic modeling

R Raman, D Pattnaik, L Hughes… - Journal of Innovation & …, 2024 - Elsevier
In a world that has rapidly transformed through the advent of artificial intelligence (AI), our
systematic review, guided by the PRISMA protocol, investigates a decade of AI research …

Machine learning methods for modelling the gasification and pyrolysis of biomass and waste

S Ascher, I Watson, S You - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Over the past two decades, the use of machine learning (ML) methods to model biomass
and waste gasification/pyrolysis has increased rapidly. Only 70 papers were published in …

Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda

R Nishant, M Kennedy, J Corbett - International Journal of Information …, 2020 - Elsevier
Artificial intelligence (AI) will transform business practices and industries and has the
potential to address major societal problems, including sustainability. Degradation of the …

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 …