Vessel Traffic Accident Forecasting Using a Combination Gray Neural Network Model
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摘要: 水上交通事故预测是水上安全的重要组成部分,目的是为了掌握水上交通事故未来的发展状况,为管理决策提供重要的理论依据。运用灰色神经网络组合模型对水上交通事故量进行预测,运用灰色模型对水上交通事故进行模拟,将结果和原始数据进行对比,计算出残差。运用BP神经网络模型对残差进行修正,得到最终预测的结果。仿真得到的2012年和2013年的水上交通事故预测量分别是270和281。实践表明,水上交通事故量呈下降趋势,但有部分年份仍有回升趋势。Abstract: The prediction of maritime accidents is an important part of maritime safety as it helps estimate future maritime accidents for management decision making .First ,a gray model was used to simulate accidents in water trans-portation .Then ,the original data were compared with the results to calculate the residuals .Finally ,the BP neural net-work model for the residual correction was applied in oeder to get the final prediction results .It was predicted that the number of water transportation accidents in 2012 and 2013 was 270 and 281 ,respectively .
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Key words:
- maritime accidents /
- gray prediction method /
- BP neural network
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