A neural network approach to measure real activities manipulation

作者：

Highlights：

• We use neural networks to measure three varieties of real activities manipulation.

• The multilayer perceptron approach outperforms traditional linear regressions.

• The multilayer perceptron approach performs better than self-organizing maps.

• Individual measures should be used instead of aggregated measures when applying linear regression.

摘要

•We use neural networks to measure three varieties of real activities manipulation.•The multilayer perceptron approach outperforms traditional linear regressions.•The multilayer perceptron approach performs better than self-organizing maps.•Individual measures should be used instead of aggregated measures when applying linear regression.

论文关键词：Real activities manipulation,Linear regression,Neural networks,Multilayer perceptron,Self-organizing maps

论文评审过程：Available online 8 November 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.10.047