摘要
针对当前石油公司在液货船安全检查和准入审查中存在的非定量、非智能评估问题,引入人工智能技术构建液货船综合安全评估(formal safety assessment,FSA)专家系统模型。该模型将FSA方法与专家系统进行组合,前者通过风险识别、风险衡准和风险量化,解决报告的非定量评估和审查的主观性问题;后者引入K最近邻算法、加权赋值算法等解决审查评估的非智能化和效率低的问题。选取官方案例进行模型检验,其结果表明提出的模型能有效地帮助石油公司实现船舶准入审查的定量化、智能化,并能显著提高审查效率,降低人工评估的主观性影响。
Aiming at the non-quantitative and non-intelligent assessment problems in the safety inspection and access review of tankers in oil companies,the artificial intelligence technology is introduced to construct the expert system model for formal safety assessment(FSA)of tankers.In the model,the FSA method is combined with the expert system.The FSA method is used to solve the problem of non-quantitative assessment and subjective review of reports through risk identification,risk balance and risk quantification;the K-nearest neighbor algorithm and the weighted assignment algorithm are introduced to the expert system to solve the problem of non-intelligence and low efficiency of review evaluation.Official cases are selected to test the model.The test results show that,the proposed model can effectively help oil companies to achieve the quantification and intelligence of ship access review,and can significantly improve the efficiency of review and reduce the subjective impact of artificial assessment.
作者
许琦
秦庭荣
马国梁
席永涛
XU Qi;QIN Tingrong;MA Guoliang;XI Yongtao(Marketing Services Co.,CNOOC Energy Technology&Services Co.,Ltd.,Tianjin 300451,China;Merchant Marine College,Shanghai Maritime University,Shanghai 201306,China)
出处
《上海海事大学学报》
北大核心
2021年第2期64-69,共6页
Journal of Shanghai Maritime University
基金
国家自然科学基金(51709168)
上海市科技创新行动计划(18DZ1206104)。
