Solving the Oil Spill Problem Using a Combination of CBR and a Summarization of SOM Ensembles

. In this paper, a forecasting system is presented. It predicts the presence of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR systems are designed to generate solutions to a certain problem by analysing historical data where previous solutions are stored. The system explained includes a novel network for data classification and retrieval. Such network works as a summarization algorithm for the results of an ensemble of Self-Organizing Maps. This algorithm, called Weighted Voting Superposition (WeVoS), is aimed to achieve the lowest topographic error in the map. The WeVoS-CBR system has been able to precisely predict the presence of oil slicks in the open sea areas of the north west of the Galician coast.

• Type: Conference
• Year: 2008
• Where: DCAI
• Authors: Aitor Mata, Emilio Corchado, Bruno Baruque
• Keywords: Case-based Reasoning Methodology, DCAI 2008, Distributed And Parallel Computing, Oil Slicks, Open Sea