|Table of Contents|

Optimization of Soybean Planting Density and Fertilizer Application Rate Based on RBF Neural Network(PDF)

《大豆科学》[ISSN:1000-9841/CN:23-1227/S]

Issue:
2020年03期
Page:
406-413
Research Field:
Publishing date:

Info

Title:
Optimization of Soybean Planting Density and Fertilizer Application Rate Based on RBF Neural Network
Author(s):
LIANG Xu-guang1WANG Fu-lin1ZHAO Hong-lei1DONG Zhi-gui2
(1.College of Engineering, Northeast Agricultural University, Harbin 150030, China; 2.College of Innovation and Entrepreneurship, Liaoning Institute of Science and Technology, Benxi 117004, China)
Keywords:
Neural network Regression Optimization Soybean Planting density Fertilizer application rate
PACS:
-
DOI:
10.11861/j.issn.1000-9841.2020.03.0406
Abstract:
In order to solve the problems of low fitting accuracy and inaccurate optimization results when soybean planting density and fertilizer application rate was optimized with the traditional regression model, this study proposed an optimization method based on RBF neural network. Soybean planting density, fertilizer application rate of N, P2O5, K2O were taken as experimental factors, and soybean yield was taken as impact indicator. An experiment of 4 factors and 5 levels was designed by the orthogonal rotation method on the seed of Heihe 43. The data of soybean yield under each treatment was obtained. The RBF neural network fitting model was constructed for the relationship between planting density, fertilizer application rate and yield, and the optimization method proposed in this paper was used to optimize this model. The optimization result was planting density 42.65×104 plants?ha-1, N fertilizer application rate 61.82 kg?ha-1, P2O5 fertilizer application rate 106.05 kg?ha-1, K2O fertilizer application rate 19.81 kg?ha-1, the yield of soybean under this combination was 3 821.48 kg?ha-1. Another experiment was carried out to verify the optimization result. The actual soybean yield at the optimal ratio was 3 742.29 kg?ha-1. The relative error between actual yield and optimum yield was -2.17%. It showed that the optimization method was effective and the optimization result was accurate.

References:

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Last Update: 2020-07-14