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2009 Fifth International Conference on Natural Computation
Research on Structural Optimization Arithmetic of Uplift Device of a Sugarcane Harvester Based on Hopfield Neural Network
Tianjian, China
August 14-August 16
ISBN: 978-0-7695-3736-8
ASCII Text
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Yizhi Hu, Yingchun Hu, "Research on Structural Optimization Arithmetic of Uplift Device of a Sugarcane Harvester Based on Hopfield Neural Network," 2013 International Conference on Computing, Networking and Communications (ICNC), vol. 1, pp. 284-288, 2009 Fifth International Conference on Natural Computation, 2009.
 
 
BibTex
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@article{ 10.1109/ICNC.2009.416,
author = {Yizhi Hu and Yingchun Hu},
title = {Research on Structural Optimization Arithmetic of Uplift Device of a Sugarcane Harvester Based on Hopfield Neural Network},
journal ={2013 International Conference on Computing, Networking and Communications (ICNC)},
volume = {1},
year = {2009},
isbn = {978-0-7695-3736-8},
pages = {284-288},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICNC.2009.416},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - 2013 International Conference on Computing, Networking and Communications (ICNC)
TI - Research on Structural Optimization Arithmetic of Uplift Device of a Sugarcane Harvester Based on Hopfield Neural Network
SN - 978-0-7695-3736-8
SP284
EP288
A1 - Yizhi Hu,
A1 - Yingchun Hu,
PY - 2009
KW - Structural optimization
KW - Hopfield Neural Network
KW - Simulated annealing
KW - whole optimization
VL - 1
JA - 2013 International Conference on Computing, Networking and Communications (ICNC)
ER -
 
The structural optimal problem of a sugarcane harvester was solved through the method combined with Hopfield Neural Network (NN) and Simulated Annealing (SA). The corresponding relationships between Neural Network and optimal problem were built, such as NN energy function and objective of optimal problem, NN evolving process and searching process of optimal design, NN equilibrium point and solution of optimal problem and so on. The improved castigatory operator was used to accelerate NN convergence. After 12 iterations, the constraints reached their boundary which showed the design resources could be used sufficiently and the whole optimal results could be received. It is proved to be an effective and reliable way to be used in engineering projects and a new idea in solving the structural optimal problems.
Index Terms:
Structural optimization, Hopfield Neural Network, Simulated annealing, whole optimization
Citation:
Yizhi Hu, Yingchun Hu, "Research on Structural Optimization Arithmetic of Uplift Device of a Sugarcane Harvester Based on Hopfield Neural Network," icnc, vol. 1, pp.284-288, 2009 Fifth International Conference on Natural Computation, 2009
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