Short-term rainfall forecasting using machine learning-based approaches of PSO-SVR, LSTM and CNN
Short-term rainfall forecasting plays an important role in hydrologic modeling and water
resource management problems such as flood warning and real time control of urban …
resource management problems such as flood warning and real time control of urban …
[HTML][HTML] Rainfall forecasting model using machine learning methods: Case study Terengganu, Malaysia
WM Ridwan, M Sapitang, A Aziz, KF Kushiar… - Ain Shams Engineering …, 2021 - Elsevier
Rainfall plays a main role in managing the water level in the reservoir. The unpredictable
amount of rainfall due to the climate change can cause either overflow or dry in the reservoir …
amount of rainfall due to the climate change can cause either overflow or dry in the reservoir …
Implementing a novel deep learning technique for rainfall forecasting via climatic variables: An approach via hierarchical clustering analysis
Variations in rainfall negatively affect crop productivity and impose severe climatic
conditions in develo** regions. Studies that focus on climatic variations such as variability …
conditions in develo** regions. Studies that focus on climatic variations such as variability …
Application of Long Short-Term Memory (LSTM) Network for seasonal prediction of monthly rainfall across Vietnam
Seasonal rainfall forecasting is important for water resources management, agriculture, and
disaster prevention. Our study aims to provide an automated deep learning method for the …
disaster prevention. Our study aims to provide an automated deep learning method for the …
A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain …
Z He, X Wen, H Liu, J Du - Journal of Hydrology, 2014 - Elsevier
Data driven models are very useful for river flow forecasting when the underlying physical
relationships are not fully understand, but it is not clear whether these data driven models …
relationships are not fully understand, but it is not clear whether these data driven models …
Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia
RC Deo, M Şahin - Atmospheric Research, 2015 - Elsevier
The prediction of future drought is an effective mitigation tool for assessing adverse
consequences of drought events on vital water resources, agriculture, ecosystems and …
consequences of drought events on vital water resources, agriculture, ecosystems and …
Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes
In this study, the application of Artificial Neural Networks (ANN) and Multiple regression
analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was …
analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was …
Adaptive neuro-fuzzy inference system for prediction of water level in reservoir
FJ Chang, YT Chang - Advances in water resources, 2006 - Elsevier
Accurate prediction of the water level in a reservoir is crucial to optimizing the management
of water resources. A neuro-fuzzy hybrid approach was used to construct a water level …
of water resources. A neuro-fuzzy hybrid approach was used to construct a water level …
Input determination for neural network models in water resources applications. Part 1—background and methodology
The use of artificial neural network (ANN) models in water resources applications has grown
considerably over the last decade. However, an important step in the ANN modelling …
considerably over the last decade. However, an important step in the ANN modelling …
An artificial neural network model for rainfall forecasting in Bangkok, Thailand
This paper presents a new approach using an Artificial Neural Network technique to improve
rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of …
rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of …