A comprehensive survey on aquila optimizer
Aquila Optimizer (AO) is a well-known nature-inspired optimization algorithm (NIOA) that
was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population …
was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population …
Nanoremediation strategies to address environmental problems
A rapid rise in population, extensive anthropogenic activities including agricultural practices,
up-scaled industrialization, massive deforestation, etc. are the leading causes of …
up-scaled industrialization, massive deforestation, etc. are the leading causes of …
Machine-learning-based prediction of oil recovery factor for experimental CO2-Foam chemical EOR: Implications for carbon utilization projects
Enhanced oil recovery (EOR) using CO 2 injection is promising with economic and
environmental benefits as an active climate-change mitigation approach. Nevertheless, the …
environmental benefits as an active climate-change mitigation approach. Nevertheless, the …
Combined machine-learning and optimization models for predicting carbon dioxide trapping indexes in deep geological formations
Emissions of carbon dioxide (CO 2) are a major source of atmospheric pollution contributing
to global warming. Carbon geological sequestration (CGS) in saline aquifers offers a …
to global warming. Carbon geological sequestration (CGS) in saline aquifers offers a …
Application of robust deep learning models to predict mine water inflow: Implication for groundwater environment management
Traditional mine water inflow prediction is characterized by a high degree of uncertainty in
model parameters and complex mechanisms involved in the water inflow process. Data …
model parameters and complex mechanisms involved in the water inflow process. Data …
Selecting Geological Formations for CO2 Storage: A Comparative Rating System
Underground storage of carbon dioxide (CO2) in geological formations plays a vital role in
carbon capture and storage (CCS) technology. It involves capturing CO2 emissions from …
carbon capture and storage (CCS) technology. It involves capturing CO2 emissions from …
Machine learning in absorption-based post-combustion carbon capture systems: A state-of-the-art review
The enormous consumption of fossil fuels from various human activities leads to a significant
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …
Data-driven machine learning models for the prediction of hydrogen solubility in aqueous systems of varying salinity: Implications for underground hydrogen storage
Hydrogen is a clean and sustainable renewable energy source with significant potential for
use in energy storage applications because of its high energy density. In particular …
use in energy storage applications because of its high energy density. In particular …
Machine learning techniques for stock price prediction and graphic signal recognition
Stock market analysis is extremely important for investors because knowing the future trend
and grasping the changing characteristics of stock prices will decrease the risk of investing …
and grasping the changing characteristics of stock prices will decrease the risk of investing …
Improved dwarf mongoose optimization algorithm using novel nonlinear control and exploration strategies
S Fu, H Huang, C Ma, J Wei, Y Li, Y Fu - Expert Systems with Applications, 2023 - Elsevier
Abstract The Dwarf Mongoose Optimization Algorithm (DMO) is a popular metaheuristic
algorithm utilized to solve real-world problems. However, DMO has limitations such as slow …
algorithm utilized to solve real-world problems. However, DMO has limitations such as slow …