首页|New Findings from Civil Engineering Faculty Describe Advances in Artificial Inte lligence (Extreme Fine-tuning and Explainable Ai Model for Non-destructive Predi ction of Concrete Compressive Strength, the Case of Concretexai Dataset)
New Findings from Civil Engineering Faculty Describe Advances in Artificial Inte lligence (Extreme Fine-tuning and Explainable Ai Model for Non-destructive Predi ction of Concrete Compressive Strength, the Case of Concretexai Dataset)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ar tificial Intelligence. According to news reporting originating in Morelia, Mexic o, by NewsRx journalists, research stated, "This groundbreaking study introduces a novel approach employing Extreme Fine -Tuning (XFT) combined with Explainable Artificial Intelligence (XAI) for the accurate, non destructive prediction of c oncrete compressive strength. By analyzing a state-of-the-art dataset containing 18,480 data points, this study developed a deep neural network that, through ex tensive hyperparameter optimization, achieves unprecedented prediction accuracy of approximately 98.7%." Funders for this research include CIC-UMSNH, Mexico, CONAHCYT, Mexico.
MoreliaMexicoNorth and Central Ameri caArtificial IntelligenceEmerging TechnologiesEngineeringMachine Learnin gCivil Engineering Faculty
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