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Knowledge Acquisition Based on Neural Networks for Performance Evaluation of Sugarcane Harvester

  • Fang-Lan Ma
  • Shang-Ping Li
  • Yu-Lin He
  • Shi Liang
  • Shan-Shan Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)

Abstract

Expertise acquisition is always the obstacle and bottleneck in the development of intelligent design system. In order to generalize and accumulate the expertise and experience of simulation analysis and experiments, the intelligent design system of sugarcane harvester is introduced. In the intelligent system of sugarcane harvester, the neural network is applied to overcome the difficulty of knowledge acquisition (KA). In this study, the application of neural network in the system is illustrated, including data predisposal, generation and management of the knowledge. An example is given to explain the application as well. The research shows using neural network can simplify the procedure of knowledge acquisition. It can also evaluate and forecast the performance of sugarcane harvester in design phrase. And it is beneficial to enhance the development success rate of the digital product and to lessen the development cost of physical prototype.

Keywords

Neural Network Training Sample Knowledge Acquisition Back Propagation Neural Network Orthogonal Experiment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fang-Lan Ma
    • 1
    • 2
  • Shang-Ping Li
    • 3
  • Yu-Lin He
    • 2
  • Shi Liang
    • 1
  • Shan-Shan Hu
    • 1
  1. 1.College of Mechanical EngineeringGuangxi UniversityNanningChina
  2. 2.College of Mechanical EngineeringChongqing UniversityChongqingChina
  3. 3.Mechanical DepartmentGuangxi Engineering InstituteLiuzhouChina

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