[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
[HTML][HTML] Machine learning for spatial analyses in urban areas: a scoping review
The challenges for sustainable cities to protect the environment, ensure economic growth,
and maintain social justice have been widely recognized. Along with the digitization …
and maintain social justice have been widely recognized. Along with the digitization …
Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia
Abstract In East Asia, air quality has been recognized as an important public health problem.
In particular, the surface concentrations of air pollutants are closely related to human life …
In particular, the surface concentrations of air pollutants are closely related to human life …
The role of natural resources in the management of environmental sustainability: Machine learning approach
This study examines the ability of Asia's natural resources to manage environmental
sustainability through digitalization. We analyse 19 Asian nations from 1990 to 2020. In …
sustainability through digitalization. We analyse 19 Asian nations from 1990 to 2020. In …
Lithological classification by hyperspectral images based on a two-layer XGBoost model, combined with a greedy algorithm
N Lin, J Fu, R Jiang, G Li, Q Yang - Remote Sensing, 2023 - mdpi.com
Lithology classification is important in mineral resource exploration, engineering geological
exploration, and disaster monitoring. Traditional laboratory methods for the qualitative …
exploration, and disaster monitoring. Traditional laboratory methods for the qualitative …
A wavelet PM2. 5 prediction system using optimized kernel extreme learning with Boruta-XGBoost feature selection
AA Heidari, M Akhoondzadeh, H Chen - Mathematics, 2022 - mdpi.com
The fine particulate matter (PM2. 5) concentration has been a vital source of info and an
essential indicator for measuring and studying the concentration of other air pollutants. It is …
essential indicator for measuring and studying the concentration of other air pollutants. It is …
Telework systematic model design for the future of work
The practice and popularity of telework has expanded significantly in the past few years,
mostly due to the COVID-19 pandemic. As a critical factor contributing to business resilience …
mostly due to the COVID-19 pandemic. As a critical factor contributing to business resilience …
Non-linear effects of the built environment and social environment on bus use among older adults in china: An application of the xgboost model
Global aging has raised increasing concerns on the health and well-being of older adults.
Public transport is a viable option to improve the mobility and quality of life among older …
Public transport is a viable option to improve the mobility and quality of life among older …
CombineDeepNet: A Deep Network for Multistep Prediction of Near-Surface PM Concentration
PM is a type of air pollutant that can cause respiratory and cardiovascular problems. Precise
PM () concentration prediction may help reduce health concerns and provide early …
PM () concentration prediction may help reduce health concerns and provide early …
Evaluation of principal features for predicting bulk and shear modulus of inorganic solids with machine learning
The modulus of elasticity describes the ability of a solid to resist external forces, and plays a
critical role in the development of new materials to maintain structural integrity. This work …
critical role in the development of new materials to maintain structural integrity. This work …