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A Neural Network Model for Predicting Cotton Yields

  • Jun Zhang
  • Yiming Wang
  • Jinping Li
  • Ping Yang
Part of the The International Federation for Information Processing book series (IFIPAICT, volume 259)

Predicting a realistic target yield is one of the critical problems in precision farming. An artificial neural network was employed to model the nonlinear relationship between cotton yield and the factors influencing yield. Using sixyear field data obtained from LuoYang Dry Land Research Center, the neural network model was developed and trained, and the RMSE for test data was 3.70%. The results indicate that the neural network model is a superior methodology for accurately setting cotton yields.

Keywords

artificial neural network precision farming cotton yield 

References

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Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Jun Zhang
    • 1
  • Yiming Wang
    • 2
  • Jinping Li
    • 1
  • Ping Yang
    • 1
  1. 1.College of InformationBeijing Union UniversityChina
  2. 2.College of Information and Electrical EngineeringChina Agricultural UniversityChina

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