Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems
作者：
Highlights：
• A dynamic weight particle swarm optimization-based sine map method is presented.
• Weight particle swarm optimization-back propagation neural network is created.
• The back propagation neural network parameters are optimized.
• The prediction accuracy of industrial robot systems is improved.
• This method has a superior performance in reliability prediction.
摘要
•A dynamic weight particle swarm optimization-based sine map method is presented.•Weight particle swarm optimization-back propagation neural network is created.•The back propagation neural network parameters are optimized.•The prediction accuracy of industrial robot systems is improved.•This method has a superior performance in reliability prediction.
论文关键词：Reliability prediction,Particle swarm optimization,Back propagation neural network,Industrial robots,Turbochargers
论文评审过程：Received 16 November 2020, Revised 24 March 2021, Accepted 24 March 2021, Available online 30 March 2021, Version of Record 10 April 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114952
