Machine learning to explore high-entropy alloys with desired enthalpy for room-temperature hydrogen storage: Prediction of density functional theory and …

S Dangwal, Y Ikeda, B Grabowski, K Edalati - Chemical Engineering …, 2024 - Elsevier
Safe and high-density storage of hydrogen, for a clean-fuel economy, can be realized by
hydride-forming materials, but these materials should be able to store hydrogen at room …

A study on friction induced tribological characteristics of steel 316 L against 100 cr6 alloy under different lubricating conditions with machine learning model

MK Gupta, ME Korkmaz, A Karolczuk, NS Ross… - Tribology …, 2024 - Elsevier
The material steadily wears away from touching surfaces when two solid entities are
constantly moving against one other. When more parameters and extreme materials are …

Synthesis of cemented paste backfill by reutilizing multiple industrial waste residues and ultrafine tailings: Strength, microstructure, and GA-GPR prediction modeling

Q Li, B Wang, L Yang, H Zhou, M Kang, R Li, X Shu - Powder Technology, 2024 - Elsevier
Industrial waste residues are increasingly reutilized in the preparation of cemented paste
backfill for reducing the cost of mine filling. Therefore, to promote the utilization of the bulk …

Improving wheat leaf nitrogen concentration (LNC) estimation across multiple growth stages using feature combination indices (FCIs) from UAV multispectral imagery

X Su, Y Nian, H Yue, Y Zhu, J Li, W Wang, Y Sheng… - Agronomy, 2024 - mdpi.com
Leaf nitrogen concentration (LNC) is a primary indicator of crop nitrogen status, closely
related to the growth and development dynamics of crops. Accurate and efficient monitoring …

High-resolution forest age map** based on forest height maps derived from GEDI and ICESat-2 space-borne lidar data

X Lin, R Shang, JM Chen, G Zhao, X Zhang… - Agricultural and Forest …, 2023 - Elsevier
Forest age is a key parameter for estimating forest growth and carbon uptake and for forest
management. Remote sensing provides indirect but useful information for map** forest …

Machine learning-based approaches for predicting the dynamic response of RC slabs under blast loads

C Zhao, Y Zhu, Z Zhou - Engineering Structures, 2022 - Elsevier
Reinforced concrete (RC) slabs as the primary force member in the engineering structure is
often subjected to the threat of terrorist attacks or industrial gas explosions. Therefore, the …

Improving prediction of groundwater quality in situations of limited monitoring data based on virtual sample generation and Gaussian process regression

J Zhang, C **ao, W Yang, X Liang, L Zhang, X Wang… - Water Research, 2024 - Elsevier
The increasing pollution of aquifers by human activities over recent decades poses a threat
to drinking water safety. While Gaussian Process Regression (GPR) is a robust tool for …

Multi-cell sensorless internal temperature estimation based on electrochemical impedance spectroscopy with Gaussian process regression for lithium-ion batteries …

SE Ezahedi, M Kharrich, J Kim - Journal of Energy Storage, 2024 - Elsevier
Recently, fire incidents due to electrical vehicle (EV) lithium-ion battery (LIB)-based energy
storages have been increasingly occurring. Preemptive diagnosis of the thermal runaway is …

Machine learning-based rainfall forecasting with multiple non-linear feature selection algorithms

P Das, DA Sachindra, K Chanda - Water Resources Management, 2022 - Springer
The present research examined the potential of two important feature selection methods,
Bayesian Networks (BN) and Recursive Feature Elimination (RFE), in identifying the …

Optimization of thermal storage performance of cascaded multi-PCMs and carbon foam energy storage system based on GPR-PSO algorithm

X Yang, Y Li, Y Ma, J Cui, J **e - Journal of Energy Storage, 2024 - Elsevier
The study is focused on the heat transfer enhancement method for a latent heat thermal
energy storage (LHTES) system with the three-stage axially cascaded multi-phase change …