A WeVoS-CBR Approach to Oil Spill Problem

The hybrid intelligent system presented here, forecasts the presence or not of oil slicks in a certain area of the open sea after an oil spill using CaseBased Reasoning methodology. The proposed CBR includes a novel network for data classification and data retrieval. Such network works as a summarization algorithm for the results of an ensemble of Visualization Induced SelfOrganizing Maps. This algorithm, called Weighted Voting Superposition (WeVoS), is mainly aimed to achieve the lowest topographic error in the map. The system uses information obtained from various satellites such as salinity, temperature, pressure, number and area of the slicks. WeVoS-CBR system has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data.

• Type: Conference
• Year: 2008
• Where: HAIS
• Authors: Emilio Corchado, Bruno Baruque, Aitor Mata, Juan M. Corchado
• Keywords: Artificial Intelligence, CaseBased Reasoning Methodology, HAIS 2008, Oil Slicks, Weighted Voting Superposition