[HTML][HTML] Flood prediction with time series data mining: Systematic review

DK Hakim, R Gernowo, AW Nirwansyah - Natural Hazards Research, 2024 - Elsevier
The global community is continuously working to minimize the impact of disasters through
various actions, including earth surveying. For example, flood-prone areas must be …

[HTML][HTML] DEM resolution effects on machine learning performance for flood probability map**

M Avand, A Kuriqi, M Khazaei… - Journal of Hydro …, 2022 - Elsevier
Floods are among the devastating natural disasters that occurred very frequently in arid
regions during the last decades. Accurate assessment of the flood susceptibility map** is …

Integrating machine learning models with comprehensive data strategies and optimization techniques to enhance flood prediction accuracy: a review

AH Akinsoji, B Adelodun, Q Adeyi, RA Salau… - Water Resources …, 2024 - Springer
The occurrence of natural disasters, accelerated by climate change, has become a
continuous menace to the environment and consequently impacts the socioeconomic well …

[HTML][HTML] Prediction of flood discharge using hybrid PSO-SVM algorithm in Barak River Basin

S Samantaray, A Sahoo, A Agnihotri - MethodsX, 2023 - Elsevier
A crucial necessity in integrated water resource management is flood forecasting. Climate
forecasts, specifically flood prediction, comprise multifaceted tasks as they are dependant on …

Prediction of flow discharge in Mahanadi River Basin, India, based on novel hybrid SVM approaches

S Samantaray, A Sahoo - Environment, Development and Sustainability, 2024 - Springer
Accurate monthly flow discharge prediction can yield significant evidence for sustainable
management of water resources systems, optimal water allocation and use, mitigating flood …

Improvement of flood susceptibility map** by introducing hybrid ensemble learning algorithms and high-resolution satellite imageries

ARMT Islam, MMR Bappi, S Alqadhi, AA Bindajam… - Natural Hazards, 2023 - Springer
Flood, a dangerous hydro-geomorphic hazard, is one of the most critically applied science
research issue. The restoration and recovery are costly and can interrupt communities' …

A comparative study on prediction of monthly streamflow using hybrid ANFIS-PSO approaches

S Samanataray, A Sahoo - KSCE Journal of Civil Engineering, 2021 - Elsevier
Monthly prediction of streamflow is a fundamental and complex hydrological phenomenon.
Accurate streamflow prediction helps in water resources planning, design, and …

Flood hazard map** using GIS-based statistical model in vulnerable riparian regions of sub-tropical environment

A Ghosh, U Chatterjee, SC Pal… - Geocarto …, 2023 - Taylor & Francis
Floods are a recurrent natural calamity that presents substantial hazards to human lives and
infrastructure. The study indicates that a significant proportion of the study area, specifically …

[HTML][HTML] Spatial prediction of current and future flood susceptibility: examining the implications of changing climates on flood susceptibility using machine learning …

N Mahdizadeh Gharakhanlou, L Perez - Entropy, 2022 - mdpi.com
The main aim of this study was to predict current and future flood susceptibility under three
climate change scenarios of RCP2. 6 (ie, optimistic), RCP4. 5 (ie, business as usual), and …

Assessment of flood frequency using statistical and hybrid neural network method: Mahanadi River Basin, India

S Samantaray, A Sahoo, A Agnihotri - Journal of the Geological Society of …, 2021 - Springer
Flooding is the most common and widespread natural hazard affecting societies around the
globe. In this context, forecasting of peak flood discharge is necessary for planning …