Explainable artificial intelligence: a comprehensive review
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
Explainable intrusion detection for cyber defences in the internet of things: Opportunities and solutions
N Moustafa, N Koroniotis, M Keshk… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The field of Explainable Artificial Intelligence (XAI) has garnered considerable research
attention in recent years, aiming to provide interpretability and confidence to the inner …
attention in recent years, aiming to provide interpretability and confidence to the inner …
Approximating XGBoost with an interpretable decision tree
O Sagi, L Rokach - Information sciences, 2021 - Elsevier
The increasing usage of machine-learning models in critical domains has recently stressed
the necessity of interpretable machine-learning models. In areas like healthcare, finary–the …
the necessity of interpretable machine-learning models. In areas like healthcare, finary–the …
Relationship between urban spatial form and seasonal land surface temperature under different grid scales
The urban heat island (UHI) effect is intensifying with increasing urbanization. As an
important representation of the UHI effect and the urban thermal environment, it is critical to …
important representation of the UHI effect and the urban thermal environment, it is critical to …
Spatial heterogeneity modeling of water quality based on random forest regression and model interpretation
F Wang, Y Wang, K Zhang, M Hu, Q Weng… - Environmental …, 2021 - Elsevier
A systematic understanding of the spatial distribution of water quality is critical for successful
watershed management; however, the limited number of physical monitoring stations has …
watershed management; however, the limited number of physical monitoring stations has …
Intrusion detection in healthcare 4.0 internet of things systems via metaheuristics optimized machine learning
Rapid developments in Internet of Things (IoT) systems have led to a wide integration of
such systems into everyday life. Systems for active real-time monitoring are especially useful …
such systems into everyday life. Systems for active real-time monitoring are especially useful …
[HTML][HTML] Estimating the maize biomass by crop height and narrowband vegetation indices derived from UAV-based hyperspectral images
Y Zhang, C Xia, X Zhang, X Cheng, G Feng, Y Wang… - Ecological …, 2021 - Elsevier
Monitoring the aboveground biomass (AGB) of maize is essential for improving site-specific
nutrient management and predicting yield to ensure food safety. A low-altitude unmanned …
nutrient management and predicting yield to ensure food safety. A low-altitude unmanned …
The explainable potential of coupling metaheuristics-optimized-xgboost and shap in revealing vocs' environmental fate
In this paper, we explore the computational capabilities of advanced modeling tools to
reveal the factors that shape the observed benzene levels and behavior under different …
reveal the factors that shape the observed benzene levels and behavior under different …
Investigating photovoltaic solar power output forecasting using machine learning algorithms
Solar power integration in electrical grids is complicated due to dependence on volatile
weather conditions. To address this issue, continuous research and development is required …
weather conditions. To address this issue, continuous research and development is required …
Predicting aqueous adsorption of organic compounds onto biochars, carbon nanotubes, granular activated carbons, and resins with machine learning
Predictive models are useful tools for aqueous adsorption research; existing models such as
multilinear regression (MLR), however, can only predict adsorption under specific …
multilinear regression (MLR), however, can only predict adsorption under specific …