Performance comparison of an LSTM-based deep learning model versus conventional machine learning algorithms for streamflow forecasting
Streamflow forecasting plays a key role in improvement of water resource allocation,
management and planning, flood warning and forecasting, and mitigation of flood damages …
management and planning, flood warning and forecasting, and mitigation of flood damages …
Deep learning data-intelligence model based on adjusted forecasting window scale: application in daily streamflow simulation
Streamflow forecasting is essential for hydrological engineering. In accordance with the
advancement of computer aids in this field, various machine learning (ML) models have …
advancement of computer aids in this field, various machine learning (ML) models have …
A short-term flood prediction based on spatial deep learning network: A case study for Xi County, China
Floods cause substantial damage across the world every year. Accurate and timely
prediction of floods can significantly minimize the loss of life and property. Recently …
prediction of floods can significantly minimize the loss of life and property. Recently …
Water level forecasting using spatiotemporal attention-based long short-term memory network
Bangladesh is in the floodplains of the Ganges, Brahmaputra, and Meghna River delta,
crisscrossed by an intricate web of rivers. Although the country is highly prone to flooding …
crisscrossed by an intricate web of rivers. Although the country is highly prone to flooding …
An intelligent early flood forecasting and prediction leveraging machine and deep learning algorithms with advanced alert system
Flood disasters are a natural occurrence around the world, resulting in numerous casualties.
It is vital to develop an accurate flood forecasting and prediction model in order to curb …
It is vital to develop an accurate flood forecasting and prediction model in order to curb …
Performance improvement of LSTM-based deep learning model for streamflow forecasting using Kalman filtering
F Bakhshi Ostadkalayeh, S Moradi, A Asadi… - Water Resources …, 2023 - Springer
Prediction of streamflow as a crucial source of hydrological information plays a central role
in various fields of water resources projects. While accurate daily streamflow forecasts are …
in various fields of water resources projects. While accurate daily streamflow forecasts are …
Exploring the best sequence LSTM modeling architecture for flood prediction
Accurate and efficient models for rainfall–runoff (RR) simulations are crucial for flood risk
management. Recently, the success of the recurrent neural network (RNN) applied to …
management. Recently, the success of the recurrent neural network (RNN) applied to …
A comparative study of Machine Learning and Deep Learning methods for flood forecasting in the Far-North region, Cameroon
Flood crises are the consequence of climate change and global warming, which lead to an
increase in the frequency and intensity of heavy rainfall. Floods are, and remain, natural …
increase in the frequency and intensity of heavy rainfall. Floods are, and remain, natural …
Tree-based machine learning algorithms in the Internet of Things environment for multivariate flood status prediction
Floods are one of the most common natural disasters in the world that affect all aspects of
life, including human beings, agriculture, industry, and education. Research for developing …
life, including human beings, agriculture, industry, and education. Research for developing …
A long Short-Term memory cyclic model with mutual information for hydrology forecasting: A Case study in the xixian basin
N Lv, X Liang, C Chen, Y Zhou, J Li, H Wei… - Advances in Water …, 2020 - Elsevier
Floods result in substantial damage throughout the world every year. An accurate
predictions of floods can significantly alleviate the loss of lives and properties. However, due …
predictions of floods can significantly alleviate the loss of lives and properties. However, due …