[HTML][HTML] Flood susceptibility mapping using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
Flood has long been known as one of the most catastrophic natural hazards worldwide.
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Mapping flood-prone areas is an important part of flood disaster management. In this study …
A comparative assessment of flood susceptibility modelling of GIS-based TOPSIS, VIKOR, and EDAS techniques in the Sub-Himalayan foothills region of Eastern India
Abstract In the Sub-Himalayan foothills region of eastern India, floods are considered the
most powerful annually occurring natural disaster, which cause severe losses to the socio …
most powerful annually occurring natural disaster, which cause severe losses to the socio …
[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 …
have heightened global concerns in light of climate change. Flood susceptibility modeling is …
Spatio-temporal modeling of PM2. 5 risk mapping using three machine learning algorithms
Urban air pollution is one of the most critical issues that affect the environment, community
health, economy, and management of urban areas. From a public health perspective, PM …
health, economy, and management of urban areas. From a public health perspective, PM …
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 …
the most widespread destruction. The purpose of the proposed research is to analyze flood …
Correct and remap solar radiation and photovoltaic power in China based on machine learning models
F Liu, X Wang, F Sun, H Wang - Applied Energy, 2022 - Elsevier
Accurate estimation of surface solar radiation (SSR) is crucial for photovoltaic (PV) systems
design and solar PV power plants site selection. However, the SSR observations often suffer …
design and solar PV power plants site selection. However, the SSR observations often suffer …
Driver drowsiness modeling based on spatial factors and electroencephalography using machine learning methods: A simulator study
F Farhangi, A Sadegh-Niaraki… - … research part F: traffic …, 2023 - Elsevier
Driver drowsiness is one of the leading causes of fatal road traffic accidents (RTA). While
studies have illustrated the effectiveness of spatial criteria on driver drowsiness, the effects …
studies have illustrated the effectiveness of spatial criteria on driver drowsiness, the effects …
Urban restaurants and online food delivery during the COVID-19 pandemic: a spatial and socio-demographic analysis
B Feizizadeh, D Omrazadeh, M Ghasemi… - … Journal of Digital …, 2023 - Taylor & Francis
In this research, we analyzed the delivery service areas of restaurants, customer satisfaction,
and restaurant sales of urban restaurants during the COVID-19 pandemic. We obtained the …
and restaurant sales of urban restaurants during the COVID-19 pandemic. We obtained the …
A spatially based machine learning algorithm for potential mapping of the hearing senses in an urban environment
M Farahani, SV Razavi-Termeh… - Sustainable Cities and …, 2022 - Elsevier
Mapping individuals' sense of hearing in the urban environment helps urban managers and
planners accomplish goals such as creating a favorable urban environment for the citizens …
planners accomplish goals such as creating a favorable urban environment for the citizens …
Spatial modeling of asthma-prone areas using remote sensing and ensemble machine learning algorithms
In this study, asthma-prone area modeling of Tehran, Iran was provided by employing three
ensemble machine learning algorithms (Bootstrap aggregating (Bagging), Adaptive …
ensemble machine learning algorithms (Bootstrap aggregating (Bagging), Adaptive …