A new CBR approach to the oil spill problem

Authors:
Juan Manuel Corchado;Aitor Mata;Juan Francisco De Paz;David Del Pozo
Affiliations:
University of Salamanca, Spain, email: corchado@usal.es;University of Salamanca, Spain, email: aitor@usal.es;University of Salamanca, Spain, email: fcdps@usal.es;University of Salamanca, Spain, email: meco007@gmail.com
Venue:
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Year:
2008

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Abstract

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 CBR cycle. CBR systems have never been used before to solve oil slicks problems. The proposed system uses information obtained from various satellites such as salinity, temperature, pressure, number and area of the slicks... OSCBR system has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data.