Predicting the Presence of Oil Slicks After an Oil Spill

Authors:
Juan Manuel Corchado;Aitor Mata
Affiliations:
Department of Computing Science and Automatic, University of Salamanca, Salamanca, Spain;Department of Computing Science and Automatic, University of Salamanca, Salamanca, Spain
Venue:
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Year:
2008

Citing 10
Cited 0

Growing cell structures—a self-organizing network for unsupervised and supervised learning

Neural Networks
FSfRT: Forecasting System for Red Tides

Applied Intelligence
eParticipative process learning: process-oriented experience management and conflict solving

Data & Knowledge Engineering - Special issue: Collaborative business process technologies
The Explanatory Power of Symbolic Similarity in Case-Based Reasoning

Artificial Intelligence Review
Case-based planning

The Knowledge Engineering Review
Distributed case-based reasoning

The Knowledge Engineering Review
Fast Iterative Kernel Principal Component Analysis

The Journal of Machine Learning Research
GerAmi: Improving Healthcare Delivery in Geriatric Residences

IEEE Intelligent Systems
Case-based retrieval to support the treatment of end stage renal failure patients

Artificial Intelligence in Medicine
Growing radial basis neural networks: merging supervised and unsupervised learning with network growth techniques

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new predicting system is presented in which the aim is to forecast the presence or not of oil slicks in a certain area of the open sea after an oil spill. In this case, the CBR methodology has been chosen to solve the problem. The system designed to predict the presence of oil slicks wraps other artificial intelligence techniques such as a Growing Radial Basis Function Networks, Growing Cell Structures and Fast Iterative Kernel Principal Components Analysis in order to develop the different phases of the CBR 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 accident. Oil Spill CBR system (OSCBR) has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data.