Increasing the Accuracy of Soil Nutrient Prediction by Improving Genetic Algorithm Backpropagation Neural Networks

Soil nutrient prediction has been eliciting increasing attention in agricultural production. Backpropagation (BP) neural networks have demonstrated remarkable ability in many prediction scenarios. However, directly utilizing BP neural networks in soil nutrient prediction may not yield promising resu...

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Bibliographic Details
Published in:	Symmetry (Basel) Vol. 15; no. 1; p. 151
Main Authors:	Liu, Yanqing, Jiang, Cuiqing, Lu, Cuiping, Wang, Zhao, Che, Wanliu
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.01.2023
Subjects:	Accuracy Agricultural production Algorithms Analysis Back propagation Back propagation networks Corn Crops Empirical analysis Genetic algorithms Irrigation Machine learning Moisture content Neural networks Nitrogen Nutrients Organic matter Phosphorus Potassium Prediction models Soil acidity Soil chemistry Soils Time series Water quality China Anhui China
ISSN:	2073-8994, 2073-8994
Online Access:	Get full text
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