Forecasting the probability of finding oil slicks using a CBR system

Authors:
Aitor Mata;Juan Manuel Corchado
Affiliations:
Department of Computing Science and Automatic, University of Salamanca, Plaza de la Merced, s/n, Salamanca, Spain;Department of Computing Science and Automatic, University of Salamanca, Plaza de la Merced, s/n, Salamanca, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

A new predicting system is presented in which the aim is to forecast the presence of oil slicks in a certain area of the open sea after an oil spill. Case-based reasoning is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to previous solved problems. In this case, the system designed to predict the presence of oil slicks 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 Case-based reasoning cycle. The proposed system uses information such as sea salinity, sea temperature, wind, currents, pressure, number and area of the slicks,.... obtained from various satellites. The system has been trained using data obtained after the Prestige oil spill, occurred in the Atlantic waters, in the northwest of Spain. The system developed has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data.