具有自动进化及优化功能的综合港口国监督选船模型

Research on automatic-update and self-improving ship targeting system for PSC

文中论述了目前中国海事局所遵循的东京备忘录港口国监督选船机制中存在的诸多不足之处,提出了结合正反馈限制广义相加模型的修正方法。该方法可以有效削弱选船机制中恶性"马太效应",并根据数据的积累进行自我进化及优化。此外,作者还提出了将船舶事故因素纳入到选船机制的思路和具体工作流程,以及包含"港口国监督检查指导建议"的选船机制的思路和实现方式。

This paper focuses on introducing a new model of PSC ship targeting system with advantages of automatic-updating and self-improving,with a view to avoiding some weak points of the current Tokyo-MOU s ship targeting system. This model can mitigate the negative effects of the Matthew Effects ,which is used in the PSC ship targeting system. In addition,the author suggests incorporating the factor of maritime accidents and Guidance on on-site inspection in the PSC ship targeting system.