Abstract
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.
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Mata, A., Corchado, E., Baruque, B. (2009). Solving the Oil Spill Problem Using a Combination of CBR and a Summarization of SOM Ensembles. In: Corchado, J.M., RodrÃguez, S., Llinas, J., Molina, J.M. (eds) International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008). Advances in Soft Computing, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85863-8_78
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DOI: https://doi.org/10.1007/978-3-540-85863-8_78
Publisher Name: Springer, Berlin, Heidelberg
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