[HTML][HTML] Flood prediction with time series data mining: Systematic review
DK Hakim, R Gernowo, AW Nirwansyah - Natural Hazards Research, 2023 - 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 …
various actions, including earth surveying. For example, flood-prone areas must be …
Prediction of flood in Barak River using hybrid machine learning approaches: a case study
A Sahoo, S Samantaray, DK Ghose - Journal of the Geological Society of …, 2021 - Springer
Flooding causes several threats with outcomes which include peril to human and animal life,
damage to property, and adversity to agricultural fields. Therefore, flood prediction is of …
damage to property, and adversity to agricultural fields. Therefore, flood prediction is of …
Forecasting of compound ocean-fluvial floods using machine learning
Flood modelling and forecasting can enhance our understanding of flood mechanisms and
facilitate effective management of flood risk. Conventional flood hazard and risk …
facilitate effective management of flood risk. Conventional flood hazard and risk …
Comparison of strategies for multistep-ahead lake water level forecasting using deep learning models
G Li, Z Shu, M Lin, J Zhang, X Yan, Z Liu - Journal of Cleaner Production, 2024 - Elsevier
Accurate forecasting of multistep-ahead lake water level is valuable for extreme disaster
prevention and eco-environmental protection. However, existing studies mainly focus on …
prevention and eco-environmental protection. However, existing studies mainly focus on …
[PDF][PDF] Deep Learning-Based Forecast and Warning of Floods in Klang River, Malaysia.
Accepted: 4 May 2020 Long short-term memory (LSTM) networks are state of the art
technique for time-series sequence learning. They are less commonly applied to the …
technique for time-series sequence learning. They are less commonly applied to the …
[PDF][PDF] Flood prediction using ARIMA model in Sungai Melaka, Malaysia
The aim of this study is to develop a flood prediction model by analyzing the real-time flood
parameters for Pengkalan Rama, Melaka river hereafter known as Sungai Melaka using the …
parameters for Pengkalan Rama, Melaka river hereafter known as Sungai Melaka using the …
Flood River Water Level Forecasting using Ensemble Machine Learning for Early Warning Systems
Flood forecasting is crucial for early warning system and disaster risk reduction. Yet the flood
river water levels are difficult and challenging task that it cannot be easily captured with …
river water levels are difficult and challenging task that it cannot be easily captured with …
Flood disaster and early warning: application of ANFIS for river water level forecasting
Intensively monitoring river water level and flows in both upstream and downstream
catchments are essential for flood forecasting in disaster risk reduction. This paper presents …
catchments are essential for flood forecasting in disaster risk reduction. This paper presents …
Comparison between NARX-NN and HEC-HMS models to simulate Wadi Seghir catchment runoff events in Algerian northern
This paper presents a comparison between the black box Nonlinear Auto-Regressive with
eXogenous inputs-Neural Network (NARX-NN) and the conceptual Hydrologic Engineering …
eXogenous inputs-Neural Network (NARX-NN) and the conceptual Hydrologic Engineering …
Flood forecasting of Malaysia Kelantan River using support vector regression technique.
The rainstorm is believed to contribute flood disasters in upstream catchments, resulting in
further consequences in downstream area due to rise of river water levels. Forecasting for …
further consequences in downstream area due to rise of river water levels. Forecasting for …