Synthesis optimization and adsorption modeling of biochar for pollutant removal via machine learning

W Zhang, R Chen, J Li, T Huang, B Wu, J Ma, Q Wen… - Biochar, 2023 - Springer
Due to large specific surface area, abundant functional groups and low cost, biochar is
widely used for pollutant removal. The adsorption performance of biochar is related to …

[HTML][HTML] Exposure to urban greenspace and pathways to respiratory health: An exploratory systematic review

W Mueller, J Milner, M Loh, S Vardoulakis… - Science of the Total …, 2022 - Elsevier
Background/objective Urban greenspace may have a beneficial or adverse effect on
respiratory health. Our objective was to perform an exploratory systematic review to …

[HTML][HTML] Flash flood detection and susceptibility mapping in the Monsoon period by integration of optical and radar satellite imagery using an improvement of a …

SV Razavi-Termeh, MB Seo, A Sadeghi-Niaraki… - Weather and Climate …, 2023 - Elsevier
Rainfall monsoons and the resulting flooding have always been cataclysmic disasters that
have heightened global concerns in light of climate change. Flood susceptibility modeling is …

Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery

SV Razavi-Termeh, A Sadeghi-Niaraki, MB Seo… - Science of The Total …, 2023 - Elsevier
Floods are the natural disaster that occurs most frequently due to the weather and causes
the most widespread destruction. The purpose of the proposed research is to analyze flood …

Estimation of maize LAI using ensemble learning and UAV multispectral imagery under different water and fertilizer treatments

Q Cheng, H Xu, S Fei, Z Li, Z Chen - Agriculture, 2022 - mdpi.com
The leaf area index (LAI), commonly used as an indicator of crop growth and physiological
development, is mainly influenced by the degree of water and fertilizer stress. Accurate …

Covid-19 risk mapping with considering socio-economic criteria using machine learning algorithms

SV Razavi-Termeh, A Sadeghi-Niaraki… - International journal of …, 2021 - mdpi.com
The reduction of population concentration in some urban land uses is one way to prevent
and reduce the spread of COVID-19 disease. Therefore, the objective of this study is to …

Spatio-temporal modeling of asthma-prone areas: Exploring the influence of urban climate factors with explainable artificial intelligence (XAI)

SV Razavi-Termeh, A Sadeghi-Niaraki, F Ali… - Sustainable Cities and …, 2024 - Elsevier
Urbanization's impact on climate is increasingly recognized as a significant public health
challenge, particularly for respiratory conditions like asthma. Despite progress in …

[HTML][HTML] Evaluation of tree-based machine learning algorithms for accident risk mapping caused by driver lack of alertness at a national scale

F Farhangi, A Sadeghi-Niaraki, SV Razavi-Termeh… - Sustainability, 2021 - mdpi.com
Drivers' lack of alertness is one of the main reasons for fatal road traffic accidents (RTA) in
Iran. Accident-risk mapping with machine learning algorithms in the geographic information …

Wildfire susceptibility mapping using deep learning algorithms in two satellite imagery dataset

N Bahadori, SV Razavi-Termeh, A Sadeghi-Niaraki… - Forests, 2023 - mdpi.com
Recurring wildfires pose a critical global issue as they undermine social and economic
stability and jeopardize human lives. To effectively manage disasters and bolster community …

People's olfactory perception potential mapping using a machine learning algorithm: A Spatio-temporal approach

M Farahani, SV Razavi-Termeh… - Sustainable Cities and …, 2023 - Elsevier
This research aimed to conduct Spatio-temporal modeling of people's olfactory perception in
the Tehran city using a machine learning-based approach considering the importance of …