Abstract
The implementation of a technique that is able to detect the real state of a structure in near real time constitutes a key research field for guaranteeing the integrity of a structure and, therefore, for safeguarding human lives. This chapter presents particle swarm optimization-based strategies for multiobjective structural damage identification. Different variations of the conventional PSO based on evolutionary concepts are implemented for detecting the damage of a structure in a multiobjective framework.
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Keywords
- Particle Swarm Optimization
- Pareto Front
- Multiobjective Optimization
- Particle Swarm Optimization Algorithm
- Damage Detection
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Perera, R., Fang, SE. (2010). Multi-objective Damage Identification Using Particle Swarm Optimization Techniques. In: Nedjah, N., dos Santos Coelho, L., de Macedo Mourelle, L. (eds) Multi-Objective Swarm Intelligent Systems. Studies in Computational Intelligence, vol 261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05165-4_8
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DOI: https://doi.org/10.1007/978-3-642-05165-4_8
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