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基于贝叶斯网络的海缆路径拖拽成本评估

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为了解决在任意海底地形条件下海缆路径拖拽成本的评估问题,采用粒子群优化算法规划海缆路径,从海缆拖拽成本相关因素入手评估海缆路径拖拽成本,建立海缆路径拖拽成本评估网络结构,并采用静态贝叶斯网络方法进行评估.在对海缆路径进行规划后,将规划出的路径相关数据离散化之后转化为贝叶斯网络评价的观测证据.然后进行仿真实验,对海缆路径的拖拽成本进行评估.最后,将仿真实验结果与实际路径结果进行比较,以验证贝叶斯网络在该领域的应用可行性.
Bayesian network based towing cost assessment for submarine cable paths
In order to solve the problem of evaluating the towing cost of submarine cable paths under arbitrary submarine terrain con-ditions,this paper adopted the particle swarm optimisation algorithm to plan submarine cable paths,evaluated the towing cost of sub-marine cable paths from the factors related to the towing cost of submarine cables,established the network structure of submarine cable paths for the evaluation of towing cost,and evaluated it with the static Bayesian network method.After the planning of the sub-marine cable path,the data related to the planned path were discretised and transformed into observation evidence for Bayesian net-work evaluation.Then,simulation experiments were conducted to evaluate the towing cost of the submarine cable path.Finally,the results of the simulation experiments were compared with the actual path results to verify the feasibility of Bayesian network appli-cation in this field.

submarine cable layingBayesian networkssubmarine cable pathspath evaluation

代青磊、李宏恩、吴尚华、黄晓明

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大连理工大学化工海洋与生命学院,辽宁 盘锦 124221

海缆铺设 贝叶斯网络 海缆路径 路径评估

2024

中国科技论文
教育部科技发展中心

中国科技论文

影响因子:0.466
ISSN:2095-2783
年,卷(期):2024.19(10)