基于SVR模型的水运化学品事故损害赔偿的研究

Damage Compensation of the Shipping Chemical Accident Based on SVR

散装化学品船舶是一种移动的危险动态源,在运输中出现的事故对人员安全和海洋环境威胁最大.因此需要结合化学品在船舶运输中的特性,对化学品泄漏污染损失额进行合理的估算,为船舶污染索赔和环境保护提供科学的理论依据.SVR作为一种基于统计学习理论的非线性回归模式,具有良好的通用性和鲁棒性,它通过算法从训练数据中抽取小的子集,建立拓扑结构,可以在有限样本下获得最优解,在解决回归、拟合等领域有着广泛的应用.本文在介绍SVR回归拟合的原理和算法的基础上,通过对实例的选取和分析,进行了水运化学品泄漏事故的风险识别和事故损害赔偿的预测,建立了SVR模型对环境风险的损失价值进行了评估.仿真结果表明,SVR在水运化学品事故损害赔偿评估中有着良好的预测性和可行性.

The bulk chemical ship is a risk of shifting dangerous source which is the greatest threat to marine safety and environment in transit when the accident occurs. Therefore, it is necessary to combine the characteristics of the chemicals in the transport for the reasonable estimate the amount of chemical spill, pollution losses for ship pollution elaims and environmental protection based on the scientific foundation. SVR is a non-linear regression model on the basis of statistical learning theory, and it has good versatility and robustness. The establishment topology is based on a small subset extracting from the training data by algorithm. The optimal solution will be obtained under the limited sample. Because of the above feature, SVR has been widely used in areas such as regression and fitting. Firstly, the basic regression and fitting principles of the SVR is introduced. Secondly, the accident damage compensation is predicted by analyzing the different examples and selecting the different kernel function. Finally, the results show that the damage compensation model is valid and feasible.