Cluster Analysis of Optimization Algorithm Based on the Athletics’ Mechanics Simulation Model of SimMechanics

Gang Peng

doi:10.4028/www.scientific.net/AMM.602-605.575

Paper Titles

Simulation of Piping Process Based on Coupling Seepage and Erosion
p.558

Numerical Simulation of Multi-Angle Incidence Aluminum Composite Targets with 7.62mm Piercing Armor
p.562

Leakage and Dispersion Modeling of Hydrogen in the Docking Process of Docking Mechanism and Exhaust Pipe of Rocket Tank
p.566

Simulation on Rationalization Process Scheduling in Large-Scale Civil Engineering
p.571

Cluster Analysis of Optimization Algorithm Based on the Athletics’ Mechanics Simulation Model of SimMechanics
p.575

Numerical Simulation of Tire Hydroplaning and its Influencing Factors
p.580

Dynamic Response of the Surface Building under the Blasting Seismic Waves
p.586

Study on the Stability of Tunnel with Large Cross Section Based on the Ultimate Strength Reduction Method
p.590

Failure Mode Analysis of Bedding Rock Slope Affected by Rock Mass Structural Plane
p.594

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Cluster Analysis of Optimization Algorithm Based...

Cluster Analysis of Optimization Algorithm Based on the Athletics’ Mechanics Simulation Model of SimMechanics

Abstract:

With the development of information technology, computer intelligence technology has been applied in all areas of life include sports biomechanics measurement field. The application of computer intelligent simulation in sports biomechanics measurement became a hot research topic in the field. The article first analyzes the principle and characteristics of cluster analysis. Based on this, it designs a simulation environment of athletics and constructs the analysis model of motion data using clustering analysis algorithm. In order to verify the practicality of the method, this paper establishes mechanical simulation model using SimMechanics. Through the analysis, we can see that the method can significantly reflect body change functions after track and the effect is significant. This method has strong practicability.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

575-579

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.575

Citation:

Cite this paper

Online since:

August 2014

Authors:

Gang Peng*

Keywords:

Athletics, Cluster Analysis, Median Follow, Simulation Analysis

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Huang Lin. Research on vector geographic data organization and indexing based on P2P network [D]. Nanjing University of Posts and Telecommunications, 2011: 2-14.

Google Scholar

[2] Yang Ming, Zhang Yiting, Luo Junzhou et al. Anonymous communication node selection algorithm based on random bandwidth weighted [J]. Journal of Southeast University (NATURAL SCIENCE EDITION), 2010(6): 1169-1173.

Google Scholar

[3] Tang Ruichun, Liu Bin, Xu Shiru et al. Node selection strategy of hierarchical P2P system based on cluster cache [J]. Journal of Ocean University of China, 2012, 40(1): 104-108.

Google Scholar

[4] Wu Jiagao, Shao Shiwei, Hua Zheng. Research and implementation of P2P network index mechanism [J]. Application of computers, 2011(9): 2301-2304.

Google Scholar

[5] Zhang Xinyue. Large-scale peer-to-peer routing system [M]. Journal of Beijing University of posts and telecommunications broad telecommunication research Center, 2011(4): 56-59.

Google Scholar

[6] Fan Xiaoping, Xiong Zheyuan, Chen Zhijie, Liu Shaoqiang, Qu Zhihua. Research on video coding in wireless multimedia sensor networks [J]. Journal of communication, 2011, 32(9): 137-146.

Google Scholar