[HTML][HTML] Recent trends of machine learning applied to multi-source data of medicinal plants

Y Zhang, Y Wang - Journal of Pharmaceutical Analysis, 2023 - Elsevier
In traditional medicine and ethnomedicine, medicinal plants have long been recognized as
the basis for materials in therapeutic applications worldwide. In particular, the remarkable …

[HTML][HTML] Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects

Y Zhang, Y Wang - Food Chemistry: X, 2023 - Elsevier
The quality and safety of edible crops are key links inseparable from human health and
nutrition. In the era of rapid development of artificial intelligence, using it to mine multi …

LBE corrosion fatigue life prediction of T91 steel and 316 SS using machine learning method assisted by symbol regression

S Feng, X Sun, G Chen, H Wu, X Chen - International Journal of Fatigue, 2023 - Elsevier
This study employs machine learning models assisted by symbol regression to achieve
satisfactory corrosion fatigue life prediction for T91 steel and 316L stainless steel (SS) used …

[HTML][HTML] Experimental investigation of three-body wear for rubber seals in abrasive slurry environment

JSK Jensen, R Aghababaei - Wear, 2023 - Elsevier
Three-body wear is a complex phenomenon occurring when abrasive particles present
between two material surfaces. By developing a new experimental setup, we systematically …

A machine learning strategy for enhancing the strength and toughness in metal matrix composites

Z Zhong, J An, D Wu, N Gao, L Liu, Z Wang… - International Journal of …, 2024 - Elsevier
Particle-reinforced metal matrix composites (MMCs) are highly sought after for various
applications due to their robust mechanical properties containing high strength and high …

Crash energy management optimization of high-speed trains by machine learning methods

S Zheng, L Jing, K Liu, Z Yu, Z Tang, K Wang - International Journal of …, 2024 - Elsevier
With the increasing speed of railway vehicles, the intricacies inherent in train collision
systems pose challenges in the rational allocation of energy during collision events. In this …

Operational reliability assessment of complex mechanical systems with multiple failure modes: An adaptive decomposition-synchronous-coordination approach

J Liu, Y Feng, C Lu, C Fei - Reliability Engineering & System Safety, 2025 - Elsevier
Abstract To effectively perform Complex Mechanical Systems Operational Reliability
Assessment (CSORA) with multiple failures, the Adaptive Decomposition-Synchronous …

[HTML][HTML] Comparative Analysis of Machine Learning Models for Predicting the Mechanical Behavior of Bio-Based Cellular Composite Sandwich Structures

D Sheini Dashtgoli, S Taghizadeh, L Macconi, F Concli - Materials, 2024 - mdpi.com
The growing demand for sustainable materials has significantly increased interest in
biocomposites, which are made from renewable raw materials and have excellent …

Mechanical characterization of soft membranes with one-shot projection moiré and metaheuristic optimization

A Boccaccio, L Lamberti, L Santoro, B Trentadue - Applied Sciences, 2023 - mdpi.com
Mechanical characterization of soft materials is a complicated inverse problem that includes
nonlinear constitutive behavior and large deformations. A further complication is introduced …

Prediction of the mechanical behaviour of HDPE pipes using the artificial neural network technique

I Srii, NB Shaik, M Jammoukh, H Ennadafy… - Engineering …, 2023 - engj.org
Actual statistics show that in recent years, more than 90% of the water distribution pipes
installed in the world are made of plastic, exclusively polyethylene (PE). Due to the …