Application Of BP Neural Network Theory In Loss Assessment Of Spilled Oil Pollution

The port economy is experiencing vigorous development at present, meanwhile we should clearly have realized that there is increasing risk of environmental pollution caused by the oil tanker behind the scenes of the prosperous port economy. In recent years, oil spill accidents continue to occur, which not only caused great economic losses to the local fisheries, aquaculture, tourism but also seriously damaged nature and ecological environment of the ocean and the coast.Whether the cost of Cleaning up oil spilled in accidents and compensation for the economic losses by environmental damage was Timely and sufficient funded to a large extent influences the oil spilled clean-up and environmental restoration activities in the efficiency and results. In China, the oil-spill accidents are not often gotten adequately compensated. Studying its root causes, we found that in addition to that China’s shipping pollution incident liability mechanism has not been well-built, there are also the lack of a standardized and scientific assessment of the pollution damage, which makes various economic and ecological damage caused by pollution accidents unable to be calculated accurately and systematically, As a result, the claimant was not paid adequately and effectively which greatly affecting the effectiveness of the clean-up, causing a hidden danger. Thus, a practical, scientific and standardized pollution assessment model for the ship oil-spill accidents are of great theoretical value and practical Significance for safeguarding the rights of the injured party, safety of life, environment of water area and the prevention of major economic losses.This paper discusses damage assessment methods on the basis of latest research status and application of oil pollution damage assessment methods at home and abroad. Direct assessment requires not only a wide variety of data but also complete and accurate ones, which to some extent, limited its practice use. Because of the complexity of nonlinear systems in Oil pollution incident assessment, the author introduces BP neural network theory to assessment of oil pollution damages, oil-spill accident cases as samples chosen and BP neural network model built up for compensation and claim in oil-spill accident. In this paper author gives a method to assess oil pollution damage according to characteristics closely related to analogy with oil pollution accidents, the extent of damage, type of oil spilled, quantity, Film area, the type and length of coast polluted, which also input BP neural network.While the sum of money demanded serve as output of the network.The results show that the application of BP neural network for oil-spill damage assessment is objective, reliable, can provide an new effective approach to settle compensation and claim problems resulting from oil-spill accidents at sea.