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Modeling a stress signal.
- Source :
- Applied Soft Computing; Jan2014, Vol. 14 Issue Part A, p53-61, 9p
- Publication Year :
- 2014
-
Abstract
- Highlights: [•] Proposed a computational stress signal predictor system to estimate a stress signal. [•] System based on support vector machine, genetic algorithm and neural network. [•] An experiment was conducted to acquire real-world stress data. [•] Features extracted from the stress data were provided as input to the system. [•] The stress signal was most similar to a hyperbolic tangent curve. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 15684946
- Volume :
- 14
- Issue :
- Part A
- Database :
- Supplemental Index
- Journal :
- Applied Soft Computing
- Publication Type :
- Academic Journal
- Accession number :
- 92511645
- Full Text :
- https://doi.org/10.1016/j.asoc.2013.09.019