Flood prediction using machine learning models: Literature review
Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …
The research on the advancement of flood prediction models contributed to risk reduction …
A review on stability analysis of continuous-time fuzzy-model-based control systems: From membership-function-independent to membership-function-dependent …
HK Lam - Engineering Applications of Artificial Intelligence, 2018 - Elsevier
This paper reviews the stability analysis of continuous-time fuzzy-model-based (FMB)
control systems, with emphasis on state-feedback control techniques, which is an essential …
control systems, with emphasis on state-feedback control techniques, which is an essential …
Simulation and forecasting of streamflows using machine learning models coupled with base flow separation
Efficient simulation of rainfall-runoff relationships is one of the most complex problems owing
to the high number of interrelated hydrological processes. It is well-known that machine …
to the high number of interrelated hydrological processes. It is well-known that machine …
Long lead time drought forecasting using lagged climate variables and a stacked long short-term memory model
Drought forecasting with a long lead time is essential for early warning systems and risk
management strategies. The use of machine learning algorithms has been proven to be …
management strategies. The use of machine learning algorithms has been proven to be …
Performance evaluation of artificial intelligence paradigms—artificial neural networks, fuzzy logic, and adaptive neuro-fuzzy inference system for flood prediction
R Tabbussum, AQ Dar - Environmental Science and Pollution Research, 2021 - Springer
Flood prediction has gained prominence world over due to the calamitous socio-economic
impacts this hazard has and the anticipated increase of its incidence in the near future …
impacts this hazard has and the anticipated increase of its incidence in the near future …
Flood discharge prediction using improved ANFIS model combined with hybrid particle swarm optimisation and slime mould algorithm
S Samantaray, P Sahoo, A Sahoo… - … Science and Pollution …, 2023 - Springer
Due to the disastrous socio-economic impacts of flood hazards and estimated rise of its
occurrences in the near future, there has been an increase in the importance of flood …
occurrences in the near future, there has been an increase in the importance of flood …
Monthly rainfall forecasting using one-dimensional deep convolutional neural network
Rainfall prediction targets the determination of rainfall conditions over a specific location. It is
considered vital for the agricultural industry and other industries. In this paper, we propose a …
considered vital for the agricultural industry and other industries. In this paper, we propose a …
Estimation of total dissolved solids (TDS) using new hybrid machine learning models
The overall quality of Groundwater (GW) is important, primarily because it determines the
suitability of water for drinking, irrigation, and domestic purposes. In this study, the adaptive …
suitability of water for drinking, irrigation, and domestic purposes. In this study, the adaptive …
A hybrid support vector regression–firefly model for monthly rainfall forecasting
A Danandeh Mehr, V Nourani… - International Journal of …, 2019 - Springer
Long-term prediction of rainfalls is one of the most challenging tasks in stochastic hydrology
owing to the highly random characteristics of rainfall events. In this paper, a novel approach …
owing to the highly random characteristics of rainfall events. In this paper, a novel approach …
Spatiotemporal analysis and predicting rainfall trends in a tropical monsoon-dominated country using MAKESENS and machine learning techniques
Spatiotemporal rainfall trend analysis as an indicator of climatic change provides critical
information for improved water resource planning. However, the spatiotemporal changing …
information for improved water resource planning. However, the spatiotemporal changing …