Application of ensemble machine learning approach to assess the factors affecting size and polydispersity index of liposomal nanoparticles
Liposome nanoparticles have emerged as promising drug delivery systems due to their
unique properties. Assessing particle size and polydispersity index (PDI) is critical for …
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
This study explores the utilization of ensemble-based soft computing techniques for
predicting the liquefaction potential of fine-grained soils. Generally, deterministic methods …
predicting the liquefaction potential of fine-grained soils. Generally, deterministic methods …
Metaheuristic-based ensemble learning: an extensive review of methods and applications
Ensemble learning has become a cornerstone in various classification and regression tasks,
leveraging its robust learning capacity across disciplines. However, the computational time …
leveraging its robust learning capacity across disciplines. However, the computational time …
Comparative performance of ensemble machine learning for Arabic cyberbullying and offensive language detection
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 …
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 …
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 …
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
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 …
and poor water solubility. Liposomes have emerged as a promising delivery system for …
Machine learning techniques applied to solar flares forecasting
Abstract Space weather encompasses the Solar-Terrestrial environment's interactions,
emphasizing phenomena in the solar environment, such as sunspots, coronal mass …
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
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 …
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
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 …
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
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 …
biological applications. Different experimental approaches have been used for measuring …