A combined thermography - Neural network for the prediction of eroded caves behind seawall

T. L. Lee, H. M. Lin, H. H. Chen, R. Y. Yang

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

Abstract

In this paper, the depth forecasting of eroded caves behind seawall model is proposed by using the back-propagation neural network combined the thermography analysis. The measured data of the depth of eroded caves behind seawall from the model experiments of sandbox and Cingcao seawall in Taiwan had been used to test the performance of the present model. From the results, it was found that the artificial neural network can efficiently forecast the depth of eroded caves behind a seawall using the four input factors, including the site temperature, humidity, thermograph area, and temperature difference

Original languageEnglish
Title of host publicationThe Proceedings of the 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE
Pages1299-1304
Number of pages6
Publication statusPublished - 2009 Dec 1
Event19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE - Osaka, Japan
Duration: 2009 Jun 212009 Jun 26

Other

Other19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE
CountryJapan
CityOsaka
Period09-06-2109-06-26

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Ocean Engineering
  • Mechanical Engineering

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    Lee, T. L., Lin, H. M., Chen, H. H., & Yang, R. Y. (2009). A combined thermography - Neural network for the prediction of eroded caves behind seawall. In The Proceedings of the 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE (pp. 1299-1304)