For Libraries For Publication Open Access Downloads About Us Contact Us
Paper Titles
Research on the Elevator System with Fault Diagnosis Method Based on Fuzzy Fault Tree
p.90
The Advances of the Prediction of the Performance and Reliability of Rolling Bearings with Poor Information
p.94
The Review of Nonlinear Dynamic Characteristics of Rolling Bearing Performances Based on Poor Information Theory
p.98
Analysis on the Effects of Atmospheric Turbulence on Line-of-Sight Ultraviolet Communication System Performance
p.102
Mechanics Analysis of Long Jump by Means of the Theory of Artificial Neural Networks
p.106
Research on Flow Sensor and the Pressure Sensor with Digital Asthma Diagnosis Technology
p.110
Aerodynamic Performance Evaluation with a New Method for Darrieus Wind Turbine
p.115
Research on Stress and Load with the Effect of Number of Teeth Planetary Gears Matching
p.120
Research on Wind Turbine Blade Loads and Dynamics Factors
p.124

Mechanics Analysis of Long Jump by Means of the Theory of Artificial Neural Networks

Article Preview

Abstract:

Takeoff is extremely important to long jump. The paper analyzes the mechanics characteristics of takeoff for long jump by means of the theory of neural network. It firstly discusses some importantly influencing factors for long jump in theory. On the basis of description of the theory of Artificial Neural Network, the back propagation network is applied to model the long jump. The results show that an excellent performance of long jump is depend on a rapid run-up speed and the rhythm of the final two steps.

You might also be interested in these eBooks
Advanced Research on Industry, Information System and Material Engineering IV View Preview

Info:

Periodical:

Advanced Materials Research (Volume 1014)

Pages:

106-109

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1014.106

Citation:

Cite this paper

Online since:

July 2014

Authors:

Qun Long Wang*

Keywords:

Long Jump, Mechanics Analysis, Neural Network (NN)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

References

[1] J. G. Hay, in: International Journal of Sport Biomechanics, Vol. 1, 1988, p.114.

Google Scholar

[2] G. Tidow, in: Track Technique, Vol. 113, 1990, p.3607.

Google Scholar

[3] T. J. Koh, and J. G. Hay, in: International Journal of Sport Biomechanics, Vol. 3, 1991, p.3756.

Google Scholar

[4] K. Mehrotra, C. K. Mohan, and S. Ranka, in: Elements of Artificial Neural Networks, MIT Press, (1997).

Google Scholar

[5] T. S. Kwak, T. Suzuki, W. B. Bae, Y. Ueharac, and H. Ohmoria, in: Journal of materials processing technology, Vol. 170, 2005, p.24.

Google Scholar

[6] İ. Asiltürk, and M. Çunkaş, in: Expert Systems with Applications, Vol. 38, 2011, p.5826.

Google Scholar

© 2025 Trans Tech Publications Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For open access content, terms of the Creative Commons licensing CC-BY are applied.
Scientific.Net is a registered trademark of Trans Tech Publications Ltd.