Research on structural optimization arithmetic of uplift device of a sugarcane harvester based on Hopfield neural network

Authors:
Yizhi Hu;Yingchun Hu
Affiliations:
Guangxi Qinglong Machine Manufacturing Corporation Limited, Guiping, Guangxi, China;Computer Science Department, Guangxi University of Technology, Liuzhou, Guangxi, China
Venue:
ICNC'09 Proceedings of the 5th international conference on Natural computation
Year:
2009

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Abstract

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.