Improved BP neural network model for predicting regional agricultural irrigation water
List of Authors
  • Lim Eng Aik , Tan Wee Choon

Keyword
  • Improved BP neural network model; BP neural network; Model solution convergence; Agricultural irrigation water prediction.

Abstract
  • The standard Backpropagation (BP) neural network model is susceptible to local convergence issues and non-convergence during the solution process. To address these challenges, wavelet analysis functions have been introduced to enhance node calculations within the standard BP neural network. This improved BP neural network model has been applied to the prediction of agricultural irrigation water. Research findings indicate that the improved BP neural network model effectively mitigates the problem of local convergence, resulting in a more reasonable solution process. Moreover, the prediction accuracy for agricultural irrigation water using the improved model is significantly higher compared to the standard BP neural network model.

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