A new improved particle swarm algorithm for optimization of anchor lattice beam support structures

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Publicado en:Natural Hazards vol. 121, no. 1 (Jan 2025), p. 225
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Springer Nature B.V.
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245 1 |a A new improved particle swarm algorithm for optimization of anchor lattice beam support structures 
260 |b Springer Nature B.V.  |c Jan 2025 
513 |a Journal Article 
520 3 |a Landslides are one of the most common natural disasters. Supporting structure plays an important role in landslide control. Slope stabilization with the application of anchor lattice beams has drawn considerable attention. However, existing structural design approaches tend to be conservative, and solutions for optimal anchor grid design are demanding. In this study, an object-oriented computer program was developed by using Python to optimize anchor lattice beam parameters in slope construction. The program utilized an improved particle swarm optimization (PSO) algorithm. It served as an efficient way to figure out the optimal parameter combination to enhance embankment construction design quality and safety. The PSO-based optimization demonstrated significant improvements in slope stability and safety, resulting in up to 30.5% average enhancement compared to non-optimized designs. Sensitivity analyses on the distance of the anchor, prestress, and angle of the anchor revealed the influence of each parameter on leading the way to appropriate anchorage conditions for anchor lattice beam support structures. 
653 |a Landslides 
653 |a Particle swarm optimization 
653 |a Structural engineering 
653 |a Embankments 
653 |a Construction 
653 |a Algorithms 
653 |a Sensitivity analysis 
653 |a Parameter sensitivity 
653 |a Optimization 
653 |a Slope stability 
653 |a Safety engineering 
653 |a Computer software 
653 |a Structural design 
653 |a Slope stabilization 
653 |a Design 
653 |a Embankment stability 
653 |a Natural disasters 
653 |a Prestressing 
653 |a Disasters 
653 |a Particle beams 
653 |a Design optimization 
653 |a Lattice design 
653 |a Environmental 
773 0 |t Natural Hazards  |g vol. 121, no. 1 (Jan 2025), p. 225 
786 0 |d ProQuest  |t Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3158255986/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
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