Research on the geometric model of Bentauron based on simulated annealing algorithm

Based on the background of the traditional folk culture activity "Bench Dragon", this paper presents mathematical modeling and optimization analysis for the marching and turning of the dragon dance team on a specific path. Firstly, this paper determines the velocity and position distribution of each bench under the condition of constant faucet speed by helix equation. Aiming at the problem of the faucet entering the turning space smoothly, this paper determines the minimum pitch which satisfies the space limitation by mathematical derivation and iterative algorithm. In order to further optimize the turning path, the optimal turning path is obtained by combining the simulated annealing algorithm and the random seed method, and the tangency between the turning curve and the spiral path is ensured. Finally, through the method of dichotomy and particle swarm optimization, the paper finds the optimal solution that the maximum traveling speed of the leader does not exceed 2 m/s, which ensures the speed coordination and safety of the whole team. The optimization scheme proposed in this paper not only ensures the smooth entry and exit of the dragon dance team in the complex path, but also improves the appreciation and practicability of the performance.

Authors

Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2024-12-25
DOI
https://doi.org/10.54097/tw332a77
Primary Topic
3D Modeling in Geospatial Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the geometric model of Bentauron based on simulated annealing algorithm

Mengyao Zhang, Shuqi Wang, Rundong Yan
Highlights in Science Engineering and Technology
3D Modeling in Geospatial Applications
article

Research on the geometric model of Bentauron based on simulated annealing algorithm

Mengyao Zhang, Shuqi Wang, Rundong Yan
article en

Abstract

Based on the background of the traditional folk culture activity "Bench Dragon", this paper presents mathematical modeling and optimization analysis for the marching and turning of the dragon dance team on a specific path. Firstly, this paper determines the velocity and position distribution of each bench under the condition of constant faucet speed by helix equation. Aiming at the problem of the faucet entering the turning space smoothly, this paper determines the minimum pitch which satisfies the space limitation by mathematical derivation and iterative algorithm. In order to further optimize the turning path, the optimal turning path is obtained by combining the simulated annealing algorithm and the random seed method, and the tangency between the turning curve and the spiral path is ensured. Finally, through the method of dichotomy and particle swarm optimization, the paper finds the optimal solution that the maximum traveling speed of the leader does not exceed 2 m/s, which ensures the speed coordination and safety of the whole team. The optimization scheme proposed in this paper not only ensures the smooth entry and exit of the dragon dance team in the complex path, but also improves the appreciation and practicability of the performance.

Highlights in Science Engineering and TechnologyVol. 120
Openalex Percentile: Top 72%
3D Modeling in Geospatial Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research on the geometric model of Bentauron based on simulated annealing algorithm — Mengyao Zhang, Shuqi Wang, et al. · Highlights in Science Engineering and Technology (2024) | TGRS Research Map | TGRS