Pareto optimal sensor locations for structural identification

By Costas Papadimitriou. 2005

116 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/634acd0221d0adbf2d55fa5d7903c3ded8272c74

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Geert Lombaert
2. Hod Lipson
3. W. Aquino
4. Josh C. Bongard
5. B. Kouchmeshky
6. Costas Papadimitriou
7. Eleni N. Chatzi
8. Oral Büyüköztürk

In Computational Theory and Mathematics

1. Geert Lombaert
2. Costas Papadimitriou

In Statistics and Probability

1. Geert Lombaert
2. Hod Lipson
3. W. Aquino
4. Josh C. Bongard
5. B. Kouchmeshky
6. Costas Papadimitriou
7. Hao Sun
8. Oral Büyüköztürk

Citations in the corpus

• Co‐evolutionary algorithm for structural damage identification using minimal physical testing (2007, background): “One approach to address this challenge is to devise strategies for optimizing the location of sensors in order to maximize the information and increase the probability of correctly detecting damage [1, 2].”
• The effect of prediction error correlation on optimal sensor placement in structural dynamics (2012, methodology): “If necessary, these estimates for the worst IEI can be improved to match the exact estimates using GAs.”