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What is MLP Neural Network for Soil Compaction about?

This study develops a multi-layer perceptron neural network model to predict modified compaction parameters (maximum dry density and optimum moisture content) for coarse-grained and fine-grained soils using 248 soil samples collected from highway construction projects. The neural network model exhibits correlation coefficients over 0.80 and 0.90 for coarse-grained and fine-grained soils respectively. The model can predict maximum dry density within ±4% and ±2% for coarse-grained and fine-grained soils, and

Author

Gaurav Verma

Language

EN