Nonlinear curve fitting to stopping power data using RBF neural networks
作者：
Highlights：
• We present a novel method using an RBF neural network with an additional linear term.
• A simple and accurate empirical formula is developed for stopping power data, based on RBF.
• A benchmark dataset is tested with the new method.
• Additional linear term improves fitting accuracy.
• The new method can be used to fit various types of data- many applications in engineering.
摘要
•We present a novel method using an RBF neural network with an additional linear term.•A simple and accurate empirical formula is developed for stopping power data, based on RBF.•A benchmark dataset is tested with the new method.•Additional linear term improves fitting accuracy.•The new method can be used to fit various types of data- many applications in engineering.
论文关键词：Radial basis function,Neural network,Curve fitting,Stopping power
论文评审过程：Received 10 October 2014, Revised 15 September 2015, Accepted 16 September 2015, Available online 9 October 2015, Version of Record 19 October 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.09.033
