A new CBR approach to the oil spill problem
نویسندگان
چکیده
Oil spills represent one of the most destructing environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be crucial in order to reduce the environmental risks. The system presented here forecasts the presence or not of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to previous solved problems. The proposed system 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 CBR cycle. CBR systems have never been used before to solve oil slicks problems. The proposed system uses information obtained from various satellites such as salinity, temperature, pressure, number and area of the slicks.... OSCBR system has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data.
منابع مشابه
Predicting the Presence of Oil Slicks After an Oil Spill
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 ...
متن کاملA 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...
متن کاملA Case-Based Reasoning System to Forecast the Presence Of Oil Slicks
After an oil spill it is essential to know if an area is going to be affected by the oil slicks generated. The system presented here forecasts the presence or not of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to...
متن کاملSolving 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 retriev...
متن کاملUsing Weibull probability distribution to calibrate prevailing wind applying in oil spill simulation
In the Persian Gulf, the major source of oil pollution is related to the transportation of tankers, offshore production and discharges by coastal refineries. The water dynamical field has been obtained using a new hydrodynamic model. Local wind is recognized as the principal driving force combining to the water dynamic field to determine oil drift on the sea surface. The Weibull probability dis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008