基于模糊贝叶斯的深远海海道测量能力结构分析

Architecture Analysis for Hydrographic Surveying Capacity in Deep Sea Based on Fuzzy Bayesian Network

针对我国深远海海道测量能力建设问题,首先对深远海海道测量能力结构进行分解,形成结构要素指标体系,利用模糊层次分析法(analytic hierarchy process,AHP),对专家的判断性语言进行模糊聚类和去模糊化处理,确定各结构要素的权重值。然后构建深远海海道测量能力评估的贝叶斯网络模型,对总体能力与其构成要素之间的关联关系进行量化分析。结果表明:在亚能力层面,深远海综合测量能力对总体能力的贡献度最高;在构成要素层面,专业化的海道测量人才队伍的贡献度最高;通过敏感性分析,海道测量科技创新,尤其是深远海测量关键技术,最容易对深远海海道测量能力产生影响。

To cope with the capacity of hydrographic survey in deep sea of China,in the present study,the capacity of hydrographic survey in deep sea is decomposed,as a result,the elements system for the capacity is established,and then,the fuzzy theory is employed to copy with expert opinion by methods of fuzzy analytic hierarchy process,obtaining the weights of all the elements.A Bayesian network is then developed to evaluate the capacity of hydrographic survey in deep sea by quantifying the relationships between the capacity and the identified elements.The results show that comprehensive hydrographic survey ability is the highest contributing factor at the sub-capacity level;with respect of element level,the professional talents for hydrographic survey are proved as the most important contributor;in addition,the technical innovations associated with hydrography,especially the key hydrographic techniques,are most likely to have an impact on the capacity of hydrographic survey in deep sea.