Modelling Nonlinear Responses of Resonance Sensors in Pressure Garment Application

Abstract : Information on the applied pressure is critical to the pressure garment treatment. The use of the passive resonance sensors would be significant improvement to existing systems. These sensors have nonlinear response and thus require nonlinear regression methods. In this paper we compare three nonlinear modelling methods: Sugeno type fuzzy inference system, support vector regression and multilayer perception networks. According to the results, all the tested methods are adequate for modelling an individual sensor. The used methods also give promising results when they are used to model responses of multiple sensors.
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Communication dans un congrès
Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.420-429, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_49〉
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Soumis le : mercredi 2 août 2017 - 16:22:28
Dernière modification le : vendredi 1 décembre 2017 - 01:16:25

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Timo Salpavaara, Pekka Kumpulainen. Modelling Nonlinear Responses of Resonance Sensors in Pressure Garment Application. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.420-429, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_49〉. 〈hal-01571487〉

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