A Dynamic Neural Network Optimization Model for Heavy Metal Content Prediction in Farmland Soil
To improve the accuracy of soil heavy metal content prediction, this study proposes a dynamic neural network optimization model (DNNOM). The model is based on a radial basis function neural network (RBFNN). The weights and bias of the output layer of the RBFNN were generated using an adaptive dynami...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9941082/ |