During pavement quality control, numerous laboratory tests such as California Bearing Ratio (CBR), Proctor compaction test, and Plasticity Index (PI) are conducted to evaluate material performance and suitability. GB PavementMat leverages advanced AI-based models developed using artificial neural networks to accurately predict these critical properties directly from sieve analysis data. This significantly reduces laboratory testing time, cost, and delays while maintaining high reliability. The combined prediction model achieves an accuracy of 97%, while the dedicated Proctor test model reaches an accuracy of 98%, delivering fast, intelligent, and dependable pavement material assessment.
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