Intelligent approaches for sustainable management and valorisation of food waste

Z Said, P Sharma, QTB Nhuong, BJ Bora… - Bioresource …, 2023 - Elsevier
Food waste (FW) is a severe environmental and social concern that today's civilization is
facing. Therefore, it is necessary to have an efficient and sustainable solution for managing …

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 …

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 …

Application of novel framework based on ensemble boosted regression trees and Gaussian process regression in modelling thermal performance of small-scale …

Z Said, P Sharma, AK Tiwari, Z Huang, VG Bui… - Journal of Cleaner …, 2022 - Elsevier
This work examined the thermal performance of a small-scale solar organic Rankine cycle
system, in which a flat plate solar collector was employed to supply heat to the organic …

State of health prediction of lithium-ion batteries based on machine learning: Advances and perspectives

X Shu, S Shen, J Shen, Y Zhang, G Li, Z Chen, Y Liu - Iscience, 2021 - cell.com
Accurate state of health (SOH) prediction is significant to guarantee operation safety and
avoid latent failures of lithium-ion batteries. With the development of communication and …

A review of modern machine learning techniques in the prediction of remaining useful life of lithium-ion batteries

P Sharma, BJ Bora - Batteries, 2022 - mdpi.com
The intense increase in air pollution caused by vehicular emissions is one of the main
causes of changing weather patterns and deteriorating health conditions. Furthermore …

[HTML][HTML] Improving the thermal efficiency of a solar flat plate collector using MWCNT-Fe3O4/water hybrid nanofluids and ensemble machine learning

Z Said, P Sharma, LS Sundar, C Li, DC Tran… - Case Studies in Thermal …, 2022 - Elsevier
The thermal performance of a flat plate solar collector using MWCNT+ Fe 3 O 4/Water hybrid
nanofluids was examined in this research. The flat plate solar collector was tested using …

Efficient wind power prediction using machine learning methods: A comparative study

A Alkesaiberi, F Harrou, Y Sun - Energies, 2022 - mdpi.com
Wind power represents a promising source of renewable energies. Precise forecasting of
wind power generation is crucial to mitigate the challenges of balancing supply and demand …

A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models

Y Alali, F Harrou, Y Sun - Scientific Reports, 2022 - nature.com
This study aims to develop an assumption-free data-driven model to accurately forecast
COVID-19 spread. Towards this end, we firstly employed Bayesian optimization to tune the …

Automated deep CNN-LSTM architecture design for solar irradiance forecasting

SMJ Jalali, S Ahmadian, A Kavousi-Fard… - … on Systems, Man …, 2021 - ieeexplore.ieee.org
Accurate prediction of solar energy is an important issue for photovoltaic power plants to
enable early participation in energy auction industries and cost-effective resource planning …