摘要
为解决长周期压力容器设备安全评估的低效率、低可靠性和不能人机交互等问题,利用开源的R语言设计复杂的神经网络识别算法,并通过C#.NET设计出一套界面友好的压力容器评估系统.实验结果表明:创建的压力容器评估系统嵌入BP神经网络算法,能精确刻画压力容器参数与状态之间的复杂非线性关系,评估准确率高;同时,软件系统实现了评估过程的交互性和自动化,具有良好的用户体验和很强的实践性.
To address the problems of low efficiency,low reliability,without human-computer interaction in the safety evaluation of the long-periodic pressure vessel,an intelligent evaluation system based on artificial neural network algorithm is established.In which the open source R language is used to design the complex neural network intelligent algorithm and a user-friendly operating system is developed through C#.NET technology.The experimental results show that the pressure vessel evaluation system embedded BP neural network algorithm can precisely figure out the complex nonlinear relationship between the parameters and the state of pressure vessel by significantly high accuracy.Meanwhile,the software system promotes the interactivity and automation of the evaluation process,which gives good user experience and strong practicality.
出处
《华侨大学学报（自然科学版）》
CAS
北大核心
2014年第5期528-532,共5页
Journal of Huaqiao University(Natural Science)
基金
福建省自然科学基金资助项目(2012J01274)
华侨大学高层次人才科研项目(09BS515)
关键词
压力容器
评估
人工神经网络
混合编程
pressure vessel
evaluation
artificial neural networks
mixed programming
