Big Bang-Big Crunch optimization for parameter estimation in structural systems

Details Big Bang-Big Crunch optimization for parameter estimation in structural systems Big Bang-Big Crunch optimization for parameter estimation in structural systems

Nov 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010mssp...24.2888t&link_type=abstract

Mechanical Systems and Signal Processing, Volume 24, Issue 8, p. 2888-2897.

Statistics

Computation

Scientific paper

A new approach to parameter estimation of structural systems using the recently developed Big Bang-Big Crunch (BB-BC) optimization is proposed, in which the parameter estimation is formulated as a multi-modal optimization problem with high dimension. The BB-BC method is inspired by one of the theories of the evolution of universe. The potentialities of BB-BC are its inherent numerical simplicity, high convergence speed, and easy implementation. The performances of the proposed method are investigated with simulation results for identifying the parameters of structural systems under conditions including limited output data, noise-polluted signals, and no priori knowledge of mass, damping, or stiffness. It is observed that BB-BC gives comparatively better results than existing methods. Moreover the method is computationally simpler.

Affiliated with

Also associated with

No associations

Rating

Big Bang-Big Crunch optimization for parameter estimation in structural systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Big Bang-Big Crunch optimization for parameter estimation in structural systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Big Bang-Big Crunch optimization for parameter estimation in structural systems will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1532175