Add to ORKGThe main goal of this work is to model flood waves based on runoff and precipitation data. We utilize data from the Smeda rivera catchment provided by the CHMI in order to build several models of flood episodes. Multilayer perceptron networks and Fuzzy system models are used and their performance is compared to traditional hydrological approaches
When issuing hydrological forecasts and warnings for individual profiles, the aim is to achieve the ...
This study presents the development of artificial neural network _ANN_ and fuzzy logic _FL_ models f...
In this study three data-driven water level forecasting models are presented and discussed. One is b...
Over the last decade, neural networks-based flood forecasts systems have been increasingly used in ...
Neuro-fuzzy systems (NFS), as part of artificial intelligence (AI) techniques, have become popular i...
Neuro-fuzzy systems (NFS), as part of artificial intelligence (AI) techniques, have become popular i...
Over the last decade, neural network-based flood forecasts systems have been increasingly used in hy...
Hydrological cycle is a highly nonlinear system which makes hydrological modeling very complicated. ...
Hydrological cycle is a highly nonlinear system which makes hydrological modeling very complicated. ...
In the last decades, several data-driven models have been developed to perform the real time flood f...
One of the most important problems in hydrology is the reliable forecasting of maximum discharge at ...
A methodology is proposed for constructing a flood forecast model using the adaptive neuro-fuzzy inf...
During recent few decades, due to the importance of the availability of water, and therefore the nec...
[[abstract]]A methodology is proposed for constructing a flood forecast model using the adaptive neu...
Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time...
When issuing hydrological forecasts and warnings for individual profiles, the aim is to achieve the ...
This study presents the development of artificial neural network _ANN_ and fuzzy logic _FL_ models f...
In this study three data-driven water level forecasting models are presented and discussed. One is b...
Over the last decade, neural networks-based flood forecasts systems have been increasingly used in ...
Neuro-fuzzy systems (NFS), as part of artificial intelligence (AI) techniques, have become popular i...
Neuro-fuzzy systems (NFS), as part of artificial intelligence (AI) techniques, have become popular i...
Over the last decade, neural network-based flood forecasts systems have been increasingly used in hy...
Hydrological cycle is a highly nonlinear system which makes hydrological modeling very complicated. ...
Hydrological cycle is a highly nonlinear system which makes hydrological modeling very complicated. ...
In the last decades, several data-driven models have been developed to perform the real time flood f...
One of the most important problems in hydrology is the reliable forecasting of maximum discharge at ...
A methodology is proposed for constructing a flood forecast model using the adaptive neuro-fuzzy inf...
During recent few decades, due to the importance of the availability of water, and therefore the nec...
[[abstract]]A methodology is proposed for constructing a flood forecast model using the adaptive neu...
Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time...
When issuing hydrological forecasts and warnings for individual profiles, the aim is to achieve the ...
This study presents the development of artificial neural network _ANN_ and fuzzy logic _FL_ models f...
In this study three data-driven water level forecasting models are presented and discussed. One is b...