S
S. M. Seyedpoor
Researcher at Shomal University
Publications - 38
Citations - 1059
S. M. Seyedpoor is an academic researcher from Shomal University. The author has contributed to research in topics: Particle swarm optimization & Multi-swarm optimization. The author has an hindex of 17, co-authored 37 publications receiving 890 citations.
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Journal ArticleDOI
A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization
TL;DR: Numerical results indicate that the combination of MSEBI and PSO can provide a reliable tool to accurately identify the multiple structural damage.
Journal ArticleDOI
Structural damage detection using an efficient correlation-based index and a modified genetic algorithm
M. Nobahari,S. M. Seyedpoor +1 more
TL;DR: An efficient optimization procedure is proposed to detect multiple damage in structural systems using a modified genetic algorithm with two new operators to accurately detect the locations and extent of the eventual damage.
Journal ArticleDOI
Optimal design of arch dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms
TL;DR: The numerical results demonstrate the high performance of the proposed strategy for optimal design of arch dams, which converges to a superior solution compared to the SPSA and PSO having a lower computation cost.
Journal ArticleDOI
Optimum shape design of arch dams for earthquake loading using a fuzzy inference system and wavelet neural networks
TL;DR: In this article, an efficient methodology is proposed to find the optimum shape of arch dams considering fluid-structure interaction subject to earthquake loading, where the earthquake load is considered by time variant ground acceleration applied in the upstream-downstream direction of the arch dam.
Journal ArticleDOI
An efficient method for structural damage detection using a differential evolution algorithm-based optimisation approach
TL;DR: In this paper, an efficient method employing the differential evolution algorithm (DEA) as an optimisation solver is presented to identify the multiple damage cases of structural systems, where natural frequency changes of a structure are considered as a criterion for damage occurrence.