Application of ensemble machine learning approach to assess the factors affecting size and polydispersity index of liposomal nanoparticles

B Hoseini, MR Jaafari, A Golabpour… - Scientific Reports, 2023 - nature.com
Liposome nanoparticles have emerged as promising drug delivery systems due to their
unique properties. Assessing particle size and polydispersity index (PDI) is critical for …

Modelling and validation of liquefaction potential index of fine-grained soils using ensemble learning paradigms

S Ghani, SC Sapkota, RK Singh, A Bardhan… - Soil Dynamics and …, 2024 - Elsevier
This study explores the utilization of ensemble-based soft computing techniques for
predicting the liquefaction potential of fine-grained soils. Generally, deterministic methods …

Metaheuristic-based ensemble learning: an extensive review of methods and applications

SS Rezk, KS Selim - Neural Computing and Applications, 2024 - Springer
Ensemble learning has become a cornerstone in various classification and regression tasks,
leveraging its robust learning capacity across disciplines. However, the computational time …

Comparative performance of ensemble machine learning for Arabic cyberbullying and offensive language detection

M Khairy, TM Mahmoud, A Omar… - Language Resources …, 2024 - Springer
Since cyberbullying impacts both individual victims and entire society, research on abusive
language and its detection has attracted attention in recent years. Because social media …

Enhancing the accuracy of the REPTree by integrating the hybrid ensemble meta-classifiers for modelling the landslide susceptibility of Idukki district, South-western …

RS A**, S Saha, A Saha, A Biju, R Costache… - Journal of the Indian …, 2022 - Springer
Idukki district, situated in the Western Ghats of Peninsular India, is one of the high landslide
susceptible zones with frequent landslide occurrences during monsoon. Though plentiful …

Optimizing nanoliposomal formulations: Assessing factors affecting entrapment efficiency of curcumin-loaded liposomes using machine learning

B Hoseini, MR Jaafari, A Golabpour… - International Journal of …, 2023 - Elsevier
Background Curcumin faces challenges in clinical applications due to its low bioavailability
and poor water solubility. Liposomes have emerged as a promising delivery system for …

Machine learning techniques applied to solar flares forecasting

F Ribeiro, ALS Gradvohl - Astronomy and Computing, 2021 - Elsevier
Abstract Space weather encompasses the Solar-Terrestrial environment's interactions,
emphasizing phenomena in the solar environment, such as sunspots, coronal mass …

Machine learning-based electric vehicle charging demand prediction using origin-destination data: A uae case study

E ElGhanam, M Hassan… - 2022 5th International …, 2022 - ieeexplore.ieee.org
Optimal prediction and coordination of the energy demand of electric vehicles (EVs) is
essential to address the energy availability and range anxiety concerns of current and …

Predicting quality of life using machine learning: Case of world happiness index

A Jannani, N Sael, F Benabbou - 2021 4th International …, 2021 - ieeexplore.ieee.org
Quality of life (QoL) is a very interesting topic, especially for policy makers and people that
are interested in general state of citizen, and it can be seen in very different ways and from …

Machine learning-based prediction for single-cell mechanics

D Nguyen, L Tao, H Ye, Y Li - Mechanics of Materials, 2023 - Elsevier
Single-cell mechanics have gained much attention due to its importance in a broad range of
biological applications. Different experimental approaches have been used for measuring …