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Risk Assessment Methods Research Of Coal Shipping Terminals Based On BP Neural Network With The Example Of Suizhong Power Plant

Posted on:2014-01-19Degree:MasterType:Thesis
Country:ChinaCandidate:Y C ZhouFull Text:PDF
GTID:2248330398452418Subject:Logistics Engineering and Management
Abstract/Summary:PDF Full Text Request
Coal in China’s energy consumption structure occupies a very important position,and it is also important energy and strategic materials in China’s industrialization and modernization development, which can not be replaced in the long term. However, because China’s coal production and consumption distribution is extremely uneven, the formation of the existing "North to south""west to east" of the coal transportation pattern is apparent. Based on cost considerations, water transport is often chose as the transportation pattern of coal, the efficiency of the coal’s transport wharf in the entire transportation process is more significant important. Therefore, nowadays power plant is still heavily dependent on coal, and issues of risks in power coal wharfs are very important.First,the paper reviews the domestic and international risk management and its use of the Field, including the status of Pier risk research, and meanwhile,risk research theorys and BP neural network theory are briefly described, which provides theoretical and practical basis for the following detailed risk assessment of coal transport terminals.Takeing Suizhong power plant pier for example, the current situation is described,and systematic risk analysis in plant coal transportation dock system to identify plants dock holds many Suizhong transport risk factors. Then, by analyzing each risk factors and through access to literature and consultation with relevant experts, on the integration and optimization of the risk factors,a more all-around and more targeted coal transport wharf risk evaluation system is established.Last,according to the characteristics of the genetic algorithm, we choose it optimize the BP neural network to establish a better network model of risk assessment.By the final run through the model,more satisfied results of the risk assessment are obtained, indicating that the established model in the power plant wharf risk evaluation have a better feasibility.Finally,this paper executs sensitivity analysis for index parameters,to determine their influence degree to assessment results and provide direction to develop risk prevention measures.
Keywords/Search Tags:Plant pier, Coal, BP neural network, Risk Assessment
PDF Full Text Request
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