中国舰船研究2024，Vol.19Issue(z2)：216-224,9.DOI:10.19693/j.issn.1673-3185.03709
基于PSO-BP神经网络的船舶生产设计软件成熟度评估方法
Maturity evaluation method of ship production design software based on PSO-BP neural network
王冲 1华德睿1
作者信息
- 1. 武汉理工大学 船海与能源动力工程学院,湖北 武汉 430063
- 折叠
摘要
Abstract
[Objective]This paper proposes a new maturity assessment model for ship production design software in order to address the problem in which the existing methods are unclear and their assessment is am-biguous.[Methods]Based on the four stages of the ship production design process,namely hull,piping,outfitting and coating,a maturity assessment system is constructed and the maturity factors at each level de-termined.Combined with the Bayesian network(BN)and fuzzy best-worst method(FBWM),a completely ob-jective weighting method is proposed to improve the accuracy of the dataset.A particle swarm optimization(PSO)algorithm is introduced to improve the back propagation(BP)neural network.The PSO optimizes the weights and thresholds of the BP neural network to avoid the local minimum problem and comprehensively evaluate the maturity of the software.[Results]The results show that the root mean square error of PSO-BP is reduced by 56.86% compared to BP.[Conclusion]The accuracy and speed of the proposed model are good enough to meet practical needs,thereby providing a new approach to software maturity assessment in the shipbuilding industry.关键词
船舶生产设计软件/软件能力成熟度模型/贝叶斯网络-模糊最优最劣法/PSO-BP神经网络Key words
ship production design software/capability maturity model for software(SW-CMM)/Bayesian network and fuzzy best-worst method/PSO-BP neural network分类
交通工程引用本文复制引用
王冲,华德睿..基于PSO-BP神经网络的船舶生产设计软件成熟度评估方法[J].中国舰船研究,2024,19(z2):216-224,9.
