Ionic liquids in pharmaceutical industry: A systematic review on applications and future perspectives
W Zhuang, K Hachem, D Bokov, MJ Ansari… - Journal of Molecular …, 2022 - Elsevier
Ionic liquids (ILs) have demonstrated incredible potential of application in various industries
such as pharmaceutics. Appropriate utilization of ILs in the pharmaceutical industry can be a …
such as pharmaceutics. Appropriate utilization of ILs in the pharmaceutical industry can be a …
State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting
The technological difficulties related with blasting operations have become increasingly
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …
Ensemble deep learning-based models to predict the resilient modulus of modified base materials subjected to wet-dry cycles
M Esmaeili-Falak, RS Benemaran - Geomechanics and …, 2023 - koreascience.kr
The resilient modulus (MR) of various pavement materials plays a significant role in the
pavement design by a mechanistic-empirical method. The MR determination is done by …
pavement design by a mechanistic-empirical method. The MR determination is done by …
Optimization of random forest through the use of MVO, GWO and MFO in evaluating the stability of underground entry-type excavations
The stability evaluation of underground entry-type excavations is a prerequisite of the entry-
type mining method, which directly affects whether workers can be provided with a safe and …
type mining method, which directly affects whether workers can be provided with a safe and …
Short-term rockburst damage assessment in burst-prone mines: an explainable XGBOOST hybrid model with SCSO algorithm
Rockburst can cause significant damage to infrastructure and equipment, and pose a
substantial risk to the safety of mine workers. Effective prediction of short-term rockburst …
substantial risk to the safety of mine workers. Effective prediction of short-term rockburst …
Convolution-based ensemble learning algorithms to estimate the bond strength of the corroded reinforced concrete
Reinforced concrete bond strength deterioration is one of the most serious problems in the
construction industry. It is one of the most common factors impacting structural deterioration …
construction industry. It is one of the most common factors impacting structural deterioration …
Short-term rockburst prediction in underground project: Insights from an explainable and interpretable ensemble learning model
Rockburst is a frequent challenge during tunnel and other underground construction and is
an extreme rock damage phenomenon. Therefore, it is very crucial to accurately estimate the …
an extreme rock damage phenomenon. Therefore, it is very crucial to accurately estimate the …
Employing a genetic algorithm and grey wolf optimizer for optimizing RF models to evaluate soil liquefaction potential
Among the research hotspots in geological/geotechnical engineering, research on the
prediction of soil liquefaction potential is still limited. In this research, several machine …
prediction of soil liquefaction potential is still limited. In this research, several machine …
Predicting tunnel squeezing using support vector machine optimized by whale optimization algorithm
The squeezing behavior of surrounding rock can be described as the time-dependent large
deformation during tunnel excavation, which appears in special geological conditions, such …
deformation during tunnel excavation, which appears in special geological conditions, such …
[HTML][HTML] Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors
Coal burst is a severe hazard that can result in fatalities and damage of facilities in
underground coal mines. To address this issue, a robust unascertained combination model …
underground coal mines. To address this issue, a robust unascertained combination model …