Oil spills represent one of the most destructing environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be crucial in order to reduce the environmental risks. The system presented here forecasts the presence or not of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to previous solved problems. The proposed system wraps other artificial intelligence techniques such as a Radial Basis Function Networks, Growing Cell Structures and Principal Components Analysis in order to develop the different phases of the...
Abstract. A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast...
A multi-agent approach is presented for identifying and forecasting the structure of the water ahead...
A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast parameter...
A new predicting system is presented in which the aim is to forecast the presence of oil slicks in a...
[EN]After an oil spill it is essential to know if an area is going to be affected by the oil slicks ...
Oil spills represent one of the most destructive environmental disasters. Predicting the possibility...
In this paper, a forecasting system is presented. It predicts the presence of oil slicks in a certai...
A new predicting system is presented in which the aim is to forecast the presence or not of oil slic...
The hybrid intelligent system presented here, forecasts the presence or not of oil slicks in a certa...
This paper presents CROS, a contingency response multi-agent system for oil spills situations. The s...
This paper presents CROS, a Contingency Response multi-agent system for Oil Spill situations. The sy...
A novel hybrid forecasting Case-Based Reasoning (CBR) system is presented in this interdisciplinary ...
A multi-agent based prediction-system is presented in which the aim is to forecast the presence of o...
The history of oil well engineering applications has revealed that the frequent operational problems...
A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast parameter...
Abstract. A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast...
A multi-agent approach is presented for identifying and forecasting the structure of the water ahead...
A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast parameter...
A new predicting system is presented in which the aim is to forecast the presence of oil slicks in a...
[EN]After an oil spill it is essential to know if an area is going to be affected by the oil slicks ...
Oil spills represent one of the most destructive environmental disasters. Predicting the possibility...
In this paper, a forecasting system is presented. It predicts the presence of oil slicks in a certai...
A new predicting system is presented in which the aim is to forecast the presence or not of oil slic...
The hybrid intelligent system presented here, forecasts the presence or not of oil slicks in a certa...
This paper presents CROS, a contingency response multi-agent system for oil spills situations. The s...
This paper presents CROS, a Contingency Response multi-agent system for Oil Spill situations. The sy...
A novel hybrid forecasting Case-Based Reasoning (CBR) system is presented in this interdisciplinary ...
A multi-agent based prediction-system is presented in which the aim is to forecast the presence of o...
The history of oil well engineering applications has revealed that the frequent operational problems...
A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast parameter...
Abstract. A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast...
A multi-agent approach is presented for identifying and forecasting the structure of the water ahead...
A hybrid neuro-symbolic problem solving model is presented in which the aim is to forecast parameter...