Experimental study on DEM parameters calibration for organic fertilizer by the particle swarm optimization - backpropagation neural networks.

Journal: Scientific reports
Published Date: Jul 15, 2025

Abstract

In order to calibrate the properties of the organic fertilizer particles, this work employs an integrated strategy that combines simulations, machine vision techniques, and physical experiments. Through physical testing, the fundamental physical characteristics of the organic fertilizer particles were identified. The initial analysis was through the Plackett-Burman test. The parameters that greatly influence the angle of repose are established. The previously identified important variables were optimized by the Central Composite Design test. The regression fitting models of the BP neural network have been developed from the data set derived from the Central Composite Design test results. Genetic algorithms (GA) and particle swarm optimization algorithms (PSO) were used to optimize the BP neural network. The RMAE and RMSE of the BP, GA - BP, PSO - BP and RSM regression models were compared and analyzed. The results showed that PSO - BP algorithm could achieve better fitting effect, and could construct a prediction model with higher accuracy and less error to analyze the repose angle of the organic fertilizer particles. The PSO - BP algorithm was used to iterate until the individual with the closest fitness was obtained. COR was 0.35, COS was 0.49, COS was 0.29 and COD was 0.38 were the optimal parameter combination.

Authors

  • Fandi Zeng
    College of Mechanical and Electronic Engineering, Shandong Agriculture and Engineering University, Jinan, 250100, China.
  • Limin Liu
    Electrical and Electronic Teaching Center, Electronics Information Engineering College, Changchun University, Changchun 130022, China.
  • Yinzeng Liu
    College of Mechanical and Electronic Engineering, Shandong Agriculture and Engineering University, Jinan, 250100, China.
  • Hongbin Bai
    College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China.
  • Chunxiao Li
    Department of Ultra sound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Hongkou District, Shanghai, China.
  • Zhihuan Zhao
    College of Mechanical and Electronic Engineering, Shandong Agriculture and Engineering University, Jinan, 250100, China. zzh2023129@126.com.

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