A neural network and post-processing for estimating the values of error data

Jihoon Lee, Yousok Kim, Se Woon Choi, Hyo Seon Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A sensor network is a key factor for successful structural health monitoring (SHM). Although stable sensor network system is deployed in the structure for measurement, it is often inevitable to face measurement faults. In order to secure the continuous evaluation of targeted structure in cases where the measurement faults occur, appropriate techniques to estimate omitted or error data are necessary. In this research, back-propagation neural network is adopted as a basic estimation method. Then, a concept of post-processing is proposed to improve an accuracy of estimation obtained from the neural network. The results of simulation to verify performance of estimation are also shown.

Original languageEnglish
Title of host publicationSENSORNETS 2013 - Proceedings of the 2nd International Conference on Sensor Networks
Pages205-208
Number of pages4
Publication statusPublished - 2013 May 30
Event2nd International Conference on Sensor Networks, SENSORNETS 2013 - Barcelona, Spain
Duration: 2013 Feb 192013 Feb 21

Publication series

NameSENSORNETS 2013 - Proceedings of the 2nd International Conference on Sensor Networks

Other

Other2nd International Conference on Sensor Networks, SENSORNETS 2013
CountrySpain
CityBarcelona
Period13/2/1913/2/21

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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  • Cite this

    Lee, J., Kim, Y., Choi, S. W., & Park, H. S. (2013). A neural network and post-processing for estimating the values of error data. In SENSORNETS 2013 - Proceedings of the 2nd International Conference on Sensor Networks (pp. 205-208). (SENSORNETS 2013 - Proceedings of the 2nd International Conference on Sensor Networks).