Abstract
The radial displacement of one or several points of the dam is an important time-varying behaviour indicator and it is a nonlinear function of hydrostatic pressure, temperature and other unexpected unknown causes. Nonlinear system identification is becoming an important tool which can be used to time-varying behaviour modelling of engineering structures. Identification and prediction of complex nonlinear structural behaviour are complex tasks for which non-parametric models are often used. The objective of this study is to develop a neuro-fuzzy identification model to predict the radial displacement of the arch dam. The ANFIS (adaptive network-based fuzzy inference system) models were developed and tested using experimental data collected during 11years. Comparing the values predicted by the ANFIS with the experimental data indicates that soft computing models provide accurate results. These models can be applied for prediction of displacement in further studies.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
