Machine learning algorithms to forecast air quality: a survey
Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is
important to develop forecasting mechanisms that can be used by the authorities, so that …
important to develop forecasting mechanisms that can be used by the authorities, so that …
Air quality prediction in smart cities using machine learning technologies based on sensor data: a review
The influence of machine learning technologies is rapidly increasing and penetrating almost
in every field, and air pollution prediction is not being excluded from those fields. This paper …
in every field, and air pollution prediction is not being excluded from those fields. This paper …
Classification of breast tumors based on histopathology images using deep features and ensemble of gradient boosting methods
MR Abbasniya, SA Sheikholeslamzadeh… - Computers and …, 2022 - Elsevier
Breast cancer is the most common cancer among women worldwide. Early-stage diagnosis
of this disease can significantly improve the efficiency of treatment. Computer-Aided …
of this disease can significantly improve the efficiency of treatment. Computer-Aided …
SwiftIDS: Real-time intrusion detection system based on LightGBM and parallel intrusion detection mechanism
D Jin, Y Lu, J Qin, Z Cheng, Z Mao - Computers & Security, 2020 - Elsevier
High-speed networks are becoming common nowadays. Naturally, a challenge that arises is
that the intrusion detection system (IDS) should timely detect attacks in huge volumes of …
that the intrusion detection system (IDS) should timely detect attacks in huge volumes of …
Air quality prediction using CNN+ LSTM-based hybrid deep learning architecture
Air pollution prediction based on variables in environmental monitoring data gains further
importance with increasing concerns about climate change and the sustainability of cities …
importance with increasing concerns about climate change and the sustainability of cities …
[HTML][HTML] Auto machine learning-based modelling and prediction of excavation-induced tunnel displacement
The influence of a deep excavation on existing shield tunnels nearby is a vital issue in
tunnelling engineering. Whereas, there lacks robust methods to predict excavation-induced …
tunnelling engineering. Whereas, there lacks robust methods to predict excavation-induced …
Spatiotemporal prediction of PM2. 5 concentrations at different time granularities using IDW-BLSTM
As air pollution becomes an increasing concern globally, governments, and research
institutions have attached great importance to air quality prediction to help give early …
institutions have attached great importance to air quality prediction to help give early …
Practical early prediction of students' performance using machine learning and eXplainable AI
Predicting students' performance in advance could help assist the learning process; if “at-
risk” students can be identified early on, educators can provide them with the necessary …
risk” students can be identified early on, educators can provide them with the necessary …
Multi-directional temporal convolutional artificial neural network for PM2. 5 forecasting with missing values: A deep learning approach
Data imputation and forecasting are the major research areas in environmental data
engineering. Solving those critical issues has an immense impact on air pollution …
engineering. Solving those critical issues has an immense impact on air pollution …
Intelligent forecasting of air quality and pollution prediction using machine learning
D Kothandaraman, N Praveena… - Adsorption Science …, 2022 - journals.sagepub.com
Air pollution consists of harmful gases and fine Particulate Matter (PM2. 5) which affect the
quality of air. This has not only become the key issues in scientific research but also turned …
quality of air. This has not only become the key issues in scientific research but also turned …