Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in Machine Learning.According to news reporting originating from Shenyang, People’s Republic of Chin a, by NewsRx correspondents, research stated, “The objective of this study is to develop a broadly applicable, high-precision, and robust prediction model for t he drying shrinkage of recycled aggregate concrete, a material that exhibits sig nificantly greater shrinkage compared to natural aggregate concrete due to its c omplex characteristics.To achieve this, the study began by selecting relevant c haracteristic parameters based on international concrete codes, followed by the application of various machine learning algorithms including Backpropagation Neu ral Network, Support Vector Machine, Random Forest, eXtreme Gradient Boosting, G aussian Process Regression, k-Nearest Neighbor, Linear Regression, and Long Shor t-Term Memory to model and forecast the drying shrinkage of recycled aggregate c oncrete.”
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