Journal Article10.1007/s10950-022-10091-y
Using metaheuristic algorithms to optimize a mixed model-based ground-motion prediction model and associated variance components
Mohsen Akhani,Shahram Pezeshk +1 more
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TL;DR: This study employed two metaheuristic optimization algorithms to estimate a mixed model-based ground-motion model (GMM) with several variance components, and shows that using the proposed algorithms provides better results compared to the existing search algorithms.
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About: This article is published in Journal of Seismology. The article was published on 04 May 2022. The article focuses on the topics: Particle swarm optimization & Metaheuristic.
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Citations
Multi-objective optimization of reinforced concrete cantilever retaining wall: a comparative study
TL;DR: In this article , the performance of four multiobjective optimization algorithms, namely non-dominated sorting genetic algorithm II (NSGA-II), multi-objective particle swarm optimization (MOPSO), strength Pareto EA II (SPEA2), and multi-Objective multi-verse optimization(MVO), in developing an optimal reinforced concrete cantilever (RCC) retaining wall was investigated.
Machine Learning Model for Estimation of Local Scour Depth around Cylindrical Bridge Piers
TL;DR: In this paper , an artificial neural network (ANN) was used to predict the scour depth around bridge piers, and the results showed that the ANN model with Bayesian regularization backpropagation training algorithm provided a better predicted scour depths with a correlation coefficient (R) equal to 0.926 for training and test stages, respectively.
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Reducing the uncertainties in the NGA-West2 ground motion models by incorporating the frequency and amplitude of the fundamental peak of the horizontal-to-vertical spectral ratio of surface ground motions
TL;DR: In this paper , a model is developed to incorporate site fundamental frequency and its corresponding amplification factor in the Next Generation Attenuation (NGA)-West2 GMMs to reduce the uncertainties.
6
Application of a multi-objective optimization model for the design of piano key weirs with a fixed dam height
TL;DR: In this paper , a multi-objective optimization model known as Non-dominated Sorting Genetic Algorithm-II was applied to determine an optimal design by maximizing hydraulic discharge while minimizing the volume of the concrete.
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Application of Metaheuristic Algorithms in Ground Motion Selection and Scaling for Time History Analysis of Structures
Mohsen Akhani,Najme Alidadi,Shahram Pezeshk +2 more
1
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