A comparative study of vibrational response based impact force localization and quantification using radial basis function network and multilayer perceptron

作者：

Highlights：

• Application of Radial Basis Function Network (RBFN) to impact force identification.

• Application of Multilayer Perceptron (MLP) to the same task.

• Accuracy, success rate and error range comparison between RBFN and MLP.

• Estimation of accuracy improvement for using RBFN in place of MLP.

摘要

•Application of Radial Basis Function Network (RBFN) to impact force identification.•Application of Multilayer Perceptron (MLP) to the same task.•Accuracy, success rate and error range comparison between RBFN and MLP.•Estimation of accuracy improvement for using RBFN in place of MLP.

论文关键词：Impact force identification,Multilayer perceptron,Neural network,Radial basis function network,Feature extraction,Time domain

论文评审过程：Received 3 March 2017, Revised 25 April 2017, Accepted 9 May 2017, Available online 10 May 2017, Version of Record 18 May 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.05.027